feat: 薄殼原則落地 + seed 下沉 API + MCP 進主庫 + 部署一致性

壓測四橫向問題修正（docs 壓測報告）：

① 薄殼原則成鐵律：能力長在 API，CLI/MCP/lib 只暴露
   - seed 下沉成 API 行為：cypher-executor POST /init/seed（一次灌 API+auth recipe），
     種子資料移到 server src/lib/api-recipe-seeds.ts，CLI 改薄殼一次呼叫
   - 解除 deployFullyOk 連坐 + init 補 seed auth recipe + update 補 seed/全 KV
   - registry SUBMISSIONS_KV 補進 REQUIRED_KV_NAMESPACES（修 20/21）

② MCP 統一帳號來源（單一 remote MCP + .env 切 MCP URL）
   - MCP 從 sibling repo 搬進 arcrun/mcp/（remote Worker，route 改 mcp.arcrun.dev）
   - config 加 mcp_url 三層解析 + getMcpUrl + DEFAULT_MCP_URL
   - 新增 acr mcp-setup：依 config 寫專案 .mcp.json（接案切資料夾自動切 MCP）
   - acr --version 改動態讀 package.json（根治漂移）

③ Deploy 一致性
   - tests/release.feature + scripts/check-release.sh
   - local-deploy.sh：CLI npm publish + auto patch bump + CHANGELOG
   - local-deploy.sh bash 3.2 相容修正（mapfile / 空陣列 set -u）
   - builtins/pnpm-lock.yaml

④ README self-hosted 同步現況（移除 R2 殘留、加 flag/env、多帳號）

CLI bump → 1.3.0

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

mcp/src/tools/arcrun_introspection.ts

@@ -0,0 +1,213 @@
+/**
+ * Introspection / debug MCP tools — LI SDD M2.2
+ *
+ * arcrun_validate_yaml          — dry-run YAML 校驗，不部署
+ * arcrun_get_execution_trace    — 看 paused workflow state（task_id 細節）
+ * arcrun_list_paused_executions — 列當前所有等 callback 的 workflow
+ * arcrun_list_recent_executions — 列某 workflow 最近 N 次執行 verdict
+ *
+ * 對應 cypher-executor 新路由（commit 989fbeb）+ 既有 /validate。
+ * 所有 tool 都需要 api_key (ak_xxx) 參數 — 跟 MCP partner-auth 的 pk_live 是兩層 auth。
+ */
+
+import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
+import { z } from "zod";
+import type { Env } from "../types.js";
+import { cypherFetch, errorResponse, successResponse } from "../lib/cypher-client.js";
+
+const apiKeyDesc =
+  "你 (用戶) 的 arcrun api_key (ak_xxx)。從 https://arcrun.dev/me 取得。注意：跟 MCP 連線用的 pk_live token 是不同層 auth — pk_live 給 MCP 用，ak_xxx 給 workflow 操作用";
+
+export function registerValidateYaml(server: McpServer, env: Env) {
+  server.tool(
+    "arcrun_validate_yaml",
+    "Dry-run YAML 校驗。不部署、無 side effect。回 {valid, errors?, nodeCount, edgeCount}。**永遠先 call 此 tool 再 push_workflow**，避免反覆 deploy 失敗。",
+    {
+      api_key: z.string().describe(apiKeyDesc),
+      graph: z.object({
+        nodes: z.array(z.unknown()).describe("workflow 節點陣列"),
+        edges: z.array(z.unknown()).describe("workflow 邊陣列 (cypher binding 三元組)"),
+      }).passthrough().describe("workflow graph object（已 parse 過 YAML 的結構，非 raw YAML string）"),
+    },
+    async ({ api_key, graph }) => {
+      try {
+        const res = await cypherFetch(env, "/validate", {
+          apiKey: api_key,
+          method: "POST",
+          body: graph,
+        });
+        const body = await res.json().catch(() => null) as {
+          valid?: boolean;
+          errors?: unknown[];
+          nodeCount?: number;
+          edgeCount?: number;
+        } | null;
+
+        if (!res.ok || !body?.valid) {
+          return errorResponse(
+            "validation_failed",
+            body?.errors ? `校驗失敗，${(body.errors as unknown[]).length} 個錯誤` : `校驗失敗 HTTP ${res.status}`,
+            [
+              "依 errors 陣列逐項修改 YAML",
+              "若 errors 提到 '未知關係詞'，看 design.md §3 列出的合法關係詞",
+              "若 errors 提到 'node 不存在'，檢查 edges 的 from/to 是否拼錯",
+            ],
+            JSON.stringify(body?.errors ?? body),
+          );
+        }
+
+        return successResponse(body, [
+          `校驗通過：${body.nodeCount} 個節點 / ${body.edgeCount} 條邊`,
+          "可以 call arcrun_push_workflow 部署了",
+        ]);
+      } catch (e) {
+        return errorResponse(
+          "internal_error",
+          `validate 內部錯：${e instanceof Error ? e.message : String(e)}`,
+          ["重試一次", "若持續失敗，告訴 leo 並貼錯誤訊息"],
+        );
+      }
+    },
+  );
+}
+
+export function registerListPausedExecutions(server: McpServer, env: Env) {
+  server.tool(
+    "arcrun_list_paused_executions",
+    "列當前 api_key 下所有 paused workflow（等 daemon callback resume 的）。給 debug 用：claude_api 等 async 零件會把 workflow 暫停，此 tool 告訴你哪些還沒回來。",
+    {
+      api_key: z.string().describe(apiKeyDesc),
+      limit: z.number().int().min(1).max(100).optional().describe("最多回幾個（預設 20，最多 100）"),
+    },
+    async ({ api_key, limit }) => {
+      try {
+        const res = await cypherFetch(env, "/executions/paused", {
+          apiKey: api_key,
+          query: limit ? { limit } : undefined,
+        });
+        const body = await res.json().catch(() => null);
+        if (!res.ok) {
+          return errorResponse(
+            "fetch_failed",
+            `撈 paused 列表失敗 HTTP ${res.status}`,
+            ["檢查 api_key 是否正確", "稍後重試"],
+            JSON.stringify(body),
+          );
+        }
+        return successResponse(body);
+      } catch (e) {
+        return errorResponse(
+          "internal_error",
+          e instanceof Error ? e.message : String(e),
+          ["重試一次"],
+        );
+      }
+    },
+  );
+}
+
+export function registerGetExecutionTrace(server: McpServer, env: Env) {
+  server.tool(
+    "arcrun_get_execution_trace",
+    "看單一 paused workflow 的 state 細節（trace、graph、context、pending_result）。task_id 從 paused 錯誤訊息或 list_paused_executions 取得。",
+    {
+      api_key: z.string().describe(apiKeyDesc),
+      task_id: z.string().describe(
+        "Paused workflow 的 task_id。來源：workflow 觸發後若 paused，error 訊息含 'waiting for task task_XXX'；或 list_paused_executions 回的 task_id 欄位",
+      ),
+    },
+    async ({ api_key, task_id }) => {
+      try {
+        const res = await cypherFetch(env, `/executions/${encodeURIComponent(task_id)}`, {
+          apiKey: api_key,
+        });
+        const body = await res.json().catch(() => null);
+
+        if (res.status === 404) {
+          return errorResponse(
+            "not_found",
+            `task_id "${task_id}" 沒對應的 paused state`,
+            [
+              "call list_paused_executions 看當前所有 paused，確認 task_id 正確",
+              "若該 workflow 不是 paused 型，看 list_recent_executions 查歷史 verdict",
+            ],
+          );
+        }
+
+        if (!res.ok) {
+          return errorResponse(
+            "fetch_failed",
+            `撈 execution trace 失敗 HTTP ${res.status}`,
+            ["檢查 task_id 格式是否正確"],
+            JSON.stringify(body),
+          );
+        }
+        return successResponse(body);
+      } catch (e) {
+        return errorResponse(
+          "internal_error",
+          e instanceof Error ? e.message : String(e),
+          ["重試一次"],
+        );
+      }
+    },
+  );
+}
+
+export function registerListRecentExecutions(server: McpServer, env: Env) {
+  server.tool(
+    "arcrun_list_recent_executions",
+    "列某 workflow 最近 N 次執行 verdict（成功 / 失敗 / duration）。資料來源是 ANALYTICS_KV 90 天保留期。",
+    {
+      api_key: z.string().describe(apiKeyDesc),
+      workflow_name: z.string().describe("workflow 名稱（acr push 時的 name 欄）"),
+      limit: z.number().int().min(1).max(100).optional().describe("最多回幾筆（預設 10，最多 100）"),
+    },
+    async ({ api_key, workflow_name, limit }) => {
+      try {
+        const res = await cypherFetch(
+          env,
+          `/workflows/${encodeURIComponent(workflow_name)}/executions`,
+          {
+            apiKey: api_key,
+            query: limit ? { limit } : undefined,
+          },
+        );
+        const body = await res.json().catch(() => null);
+
+        if (res.status === 404) {
+          return errorResponse(
+            "not_found",
+            `workflow "${workflow_name}" 不存在或不屬於你`,
+            [
+              "call list_workflows 看你有什麼 workflow",
+              "確認 workflow 名稱拼寫正確",
+            ],
+          );
+        }
+        if (!res.ok) {
+          return errorResponse(
+            "fetch_failed",
+            `撈執行歷史失敗 HTTP ${res.status}`,
+            ["稍後重試"],
+            JSON.stringify(body),
+          );
+        }
+        return successResponse(body);
+      } catch (e) {
+        return errorResponse(
+          "internal_error",
+          e instanceof Error ? e.message : String(e),
+          ["重試一次"],
+        );
+      }
+    },
+  );
+}
+
+export function registerAllIntrospectionTools(server: McpServer, env: Env) {
+  registerValidateYaml(server, env);
+  registerListPausedExecutions(server, env);
+  registerGetExecutionTrace(server, env);
+  registerListRecentExecutions(server, env);
+}

mcp/src/tools/arcrun_report_feedback.ts

@@ -0,0 +1,147 @@
+/**
+ * arcrun_report_feedback — explicit feedback tool for AI agents
+ *
+ * 對應 SDD .agents/specs/llm-interface/ M1.3
+ *
+ * AI agent 每次完成 workflow / 卡住 / 解掉問題後 **MUST** call 此 tool。
+ * 結構化 issue_type enum 防自由文字難聚合。寫入 KBDB type=agent-feedback block。
+ *
+ * 後續 M4 weekly_review workflow 聚合這些 block 產出 arcrun-roadmap。
+ *
+ * 命名注意：M5 全面 rename u6u → arcrun 前，本 tool 直接用新名 arcrun_ prefix
+ * 立下範例。其他 u6u_* tool 等 M5 一次切。
+ */
+
+import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
+import { z } from "zod";
+import { Env } from "../types.js";
+import { kbdbFetch } from "../lib/kbdb-client.js";
+
+const ISSUE_TYPES = [
+  "success_story",        // 順利完成，值得記錄這個 pattern
+  "doc_unclear",          // AGENTS.md / skill / contract 講不清楚
+  "tool_missing",         // 該有的 MCP tool 沒有
+  "error_unhelpful",      // 錯誤訊息看不懂下一步
+  "unexpected_behavior",  // 跟我預期的不一樣
+  "feature_request",      // 我想要 X 功能
+] as const;
+
+export function registerReportFeedback(server: McpServer, env: Env, orgNamespace: string) {
+  server.tool(
+    "arcrun_report_feedback",
+    "AI agent 完成 workflow 任務 / 卡住 / 解掉問題後 **必須** call 此 tool 回報。即使順利也要 call (issue_type=success_story)，那是告訴平台「這 pattern 已 work，可推廣」。回饋會寫進 KBDB type=agent-feedback，週報自動聚合產出平台改善 roadmap。",
+    {
+      issue_type: z.enum(ISSUE_TYPES).describe(
+        "回報類型。success_story=順利做完 / doc_unclear=文件不清楚 / tool_missing=該有的 MCP tool 缺 / error_unhelpful=錯誤訊息看不懂下一步 / unexpected_behavior=與預期不符 / feature_request=想要新功能"
+      ),
+      description: z.string().min(10).describe(
+        "詳述：你做了什麼、發生什麼、為什麼這算 issue / story。至少 10 字。若是 success_story，描述 pattern 與適用情境"
+      ),
+      workflow_name: z.string().optional().describe("相關 workflow 名稱（若有）"),
+      retry_count: z.number().int().min(0).optional().describe("為了搞定，你重試了幾次（含修 YAML / 改參數）"),
+      blocked: z.boolean().optional().describe("是否完全擋住（true = 無法繼續），預設 false"),
+      suggested_fix: z.string().optional().describe("你建議的修補方向（optional，但很有價值）"),
+      agent_user_agent: z.string().optional().describe(
+        "你（AI agent）的 client 識別字串。e.g. 'claude-code/1.x'、'cursor-mcp/0.4'、'mira-bot'。讓平台知道哪個 AI 客戶端踩到問題"
+      ),
+    },
+    async ({ issue_type, description, workflow_name, retry_count, blocked, suggested_fix, agent_user_agent }) => {
+      try {
+        if (!env.KBDB) {
+          return { content: [{ type: "text", text: "Error: KBDB service binding unavailable" }], isError: true };
+        }
+
+        const blockBody = {
+          api_key: env.PLATFORM_API_KEY || undefined,  // 若 platform key 在，聚集；否則用用戶 namespace
+          type: "agent-feedback",
+          source: "mcp-tool-call",
+          user_id: orgNamespace,
+          content: description,
+          metadata_json: JSON.stringify({
+            issue_type,
+            workflow_name,
+            retry_count,
+            blocked: blocked ?? false,
+            suggested_fix,
+            agent_user_agent,
+            reported_at: new Date().toISOString(),
+          }),
+          tags_json: JSON.stringify([
+            "agent-feedback",
+            `issue:${issue_type}`,
+            ...(blocked ? ["blocked"] : []),
+            ...(workflow_name ? [`wf:${workflow_name}`] : []),
+          ]),
+        };
+
+        // 走 KBDB service binding（既有 pattern）
+        const createResp = await kbdbFetch(env, `/blocks`, {
+          method: "POST",
+          headers: { "Content-Type": "application/json" },
+          body: JSON.stringify(blockBody),
+        });
+
+        if (!createResp.ok) {
+          const errBody = await createResp.text();
+          return {
+            content: [
+              {
+                type: "text",
+                text: JSON.stringify({
+                  ok: false,
+                  error_code: "kbdb_write_failed",
+                  human_message: `回饋寫入 KBDB 失敗：HTTP ${createResp.status}`,
+                  next_actions: [
+                    "確認 KBDB 服務在線（試 https://kbdb-get.arcrun.dev/health）",
+                    "若持續失敗，可暫先在本地記下回饋，稍後重試",
+                  ],
+                  detail: errBody.slice(0, 200),
+                }, null, 2),
+              },
+            ],
+            isError: true,
+          };
+        }
+
+        const data = await createResp.json().catch(() => null);
+
+        return {
+          content: [
+            {
+              type: "text",
+              text: JSON.stringify({
+                ok: true,
+                data: {
+                  reported: true,
+                  issue_type,
+                  block_id: (data as { id?: string } | null)?.id,
+                },
+                hints: [
+                  issue_type === "success_story"
+                    ? "感謝記錄成功 pattern！這會被納入週報自動推廣。"
+                    : "感謝回報！平台週報會聚合這類問題（M4 完成後可看 arcrun-roadmap block）",
+                  "若還有相關問題（例如同 workflow 不同 issue），可繼續 call",
+                ],
+              }, null, 2),
+            },
+          ],
+        };
+      } catch (error) {
+        return {
+          content: [
+            {
+              type: "text",
+              text: JSON.stringify({
+                ok: false,
+                error_code: "internal_error",
+                human_message: `report_feedback 內部錯誤：${error instanceof Error ? error.message : String(error)}`,
+                next_actions: ["重試一次", "若持續失敗，請告訴用戶這個 issue 並貼錯誤訊息給 leo"],
+              }, null, 2),
+            },
+          ],
+          isError: true,
+        };
+      }
+    }
+  );
+}

mcp/src/tools/arcrun_skills_examples.ts

@@ -0,0 +1,315 @@
+/**
+ * Skills + Examples lookup MCP tools — LI SDD M3.2
+ *
+ * 對應 .agents/specs/llm-interface/ Milestone 3.2 + 3.4。
+ *
+ * - arcrun_list_skills      — 列 KBDB type=agent-skill 全部
+ * - arcrun_get_skill        — 用 slug 拿 skill markdown 全文
+ * - arcrun_list_examples    — 列 KBDB type=workflow-example 全部
+ * - arcrun_get_example      — 用 slug 拿 example yaml + description + tags
+ * - arcrun_search_examples  — 自然語言 use case → 命中相關 example
+ *
+ * Skills / examples 由 arcrun/scripts/sync-registry-to-kbdb.py 從
+ * arcrun/registry/{skills,examples} 同步進 KBDB。
+ *
+ * 直接走 KBDB service binding（既有 pattern），不經 cypher-executor。
+ */
+
+import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
+import { z } from "zod";
+import type { Env } from "../types.js";
+import { kbdbFetch } from "../lib/kbdb-client.js";
+import { errorResponse, successResponse } from "../lib/cypher-client.js";
+
+interface KbdbBlock {
+  id: string;
+  page_name?: string | null;
+  content?: string | null;
+  type?: string;
+  tags_json?: string;
+  metadata_json?: string | null;
+  source?: string | null;
+  updated_at?: number;
+}
+
+async function kbdbList(env: Env, type: string, limit = 100): Promise<KbdbBlock[]> {
+  const resp = await kbdbFetch(env, `/blocks?type=${type}&limit=${limit}`);
+  if (!resp.ok) throw new Error(`KBDB list type=${type} HTTP ${resp.status}`);
+  const data = await resp.json<{ blocks?: KbdbBlock[] }>();
+  return data.blocks ?? [];
+}
+
+async function kbdbGetByPageName(env: Env, pageName: string): Promise<KbdbBlock | null> {
+  const resp = await kbdbFetch(env, `/blocks?page_name=${encodeURIComponent(pageName)}&limit=1`);
+  if (!resp.ok) return null;
+  const data = await resp.json<{ blocks?: KbdbBlock[] }>();
+  return data.blocks?.[0] ?? null;
+}
+
+function parseTags(tagsJson?: string): string[] {
+  if (!tagsJson) return [];
+  try {
+    const arr = JSON.parse(tagsJson);
+    return Array.isArray(arr) ? arr : [];
+  } catch {
+    return [];
+  }
+}
+
+export function registerListSkills(server: McpServer, env: Env) {
+  server.tool(
+    "arcrun_list_skills",
+    "列所有 agent-skill blocks（從 arcrun/registry/skills/ 同步進 KBDB）。每個 skill 是個 markdown playbook，描述 AI 面對 X 問題該怎麼想 + 該用哪個 example。回 [{slug, title, tags}]。call get_skill(slug) 拿完整內文。",
+    {
+      tag: z.string().optional().describe("optional 標籤過濾。如 'rag' / 'watcher' / 'debug'"),
+    },
+    async ({ tag }) => {
+      try {
+        const blocks = await kbdbList(env, "agent-skill", 100);
+        const skills = blocks
+          .map((b) => {
+            const tags = parseTags(b.tags_json);
+            let title = b.page_name?.replace(/^skill-/, "") ?? "(no title)";
+            try {
+              const meta = b.metadata_json ? JSON.parse(b.metadata_json) : null;
+              if (meta?.title) title = meta.title;
+            } catch {}
+            return {
+              slug: b.page_name?.replace(/^skill-/, "") ?? "",
+              page_name: b.page_name,
+              title,
+              tags,
+              chars: (b.content ?? "").length,
+            };
+          })
+          .filter((s) => !tag || s.tags.includes(`skill:${tag}`) || s.tags.includes(tag) || s.slug.includes(tag));
+
+        return successResponse(
+          { count: skills.length, skills },
+          [
+            skills.length === 0
+              ? "沒有 skill 命中。試 list_skills() 不帶 tag 看全部"
+              : "call arcrun_get_skill(slug) 拿單個 skill 完整 markdown",
+          ],
+        );
+      } catch (e) {
+        return errorResponse(
+          "fetch_failed",
+          e instanceof Error ? e.message : String(e),
+          ["稍後重試", "若持續失敗，告訴 leo"],
+        );
+      }
+    },
+  );
+}
+
+export function registerGetSkill(server: McpServer, env: Env) {
+  server.tool(
+    "arcrun_get_skill",
+    "拿單一 agent-skill 完整 markdown playbook。slug 從 list_skills 取得。",
+    {
+      slug: z.string().describe("skill slug，例如 'build_watcher_workflow' / 'rag_with_arcrun'"),
+    },
+    async ({ slug }) => {
+      try {
+        const pageName = slug.startsWith("skill-") ? slug : `skill-${slug}`;
+        const block = await kbdbGetByPageName(env, pageName);
+        if (!block) {
+          return errorResponse(
+            "not_found",
+            `skill "${slug}" 不存在`,
+            [
+              "call arcrun_list_skills() 看可用 slug",
+              "確認拼字正確（不需要 'skill-' prefix）",
+            ],
+          );
+        }
+        return successResponse({
+          slug,
+          page_name: block.page_name,
+          content: block.content,
+          tags: parseTags(block.tags_json),
+        });
+      } catch (e) {
+        return errorResponse(
+          "fetch_failed",
+          e instanceof Error ? e.message : String(e),
+          ["稍後重試"],
+        );
+      }
+    },
+  );
+}
+
+export function registerListExamples(server: McpServer, env: Env) {
+  server.tool(
+    "arcrun_list_examples",
+    "列所有 workflow-example blocks（從 arcrun/registry/examples/ 同步進 KBDB）。每個 example 是可直接 push 的 workflow YAML 範本 + description。回 [{slug, tags}]。call get_example / search_examples 拿細節。",
+    {
+      tag: z.string().optional().describe("optional 標籤過濾。如 'rag' / 'cron' / 'llm' / 'webhook'"),
+    },
+    async ({ tag }) => {
+      try {
+        const blocks = await kbdbList(env, "workflow-example", 200);
+        const examples = blocks
+          .map((b) => {
+            const tags = parseTags(b.tags_json);
+            return {
+              slug: b.page_name?.replace(/^example-/, "") ?? "",
+              page_name: b.page_name,
+              tags,
+              chars: (b.content ?? "").length,
+            };
+          })
+          .filter((e) => !tag || e.tags.includes(tag) || e.tags.includes(`example:${tag}`) || e.slug.includes(tag));
+
+        return successResponse(
+          { count: examples.length, examples },
+          [
+            examples.length === 0
+              ? "沒有 example 命中。試 list_examples() 不帶 tag 看全部"
+              : "call arcrun_get_example(slug) 拿單個 YAML + description",
+          ],
+        );
+      } catch (e) {
+        return errorResponse(
+          "fetch_failed",
+          e instanceof Error ? e.message : String(e),
+          ["稍後重試"],
+        );
+      }
+    },
+  );
+}
+
+export function registerGetExample(server: McpServer, env: Env) {
+  server.tool(
+    "arcrun_get_example",
+    "拿單一 workflow-example 完整 YAML + description。slug 從 list_examples / search_examples 取得。可直接拿 YAML 改成你自己的 → push。",
+    {
+      slug: z.string().describe("example slug，例如 'rag-search-answer' / 'cron-watcher'"),
+    },
+    async ({ slug }) => {
+      try {
+        const pageName = slug.startsWith("example-") ? slug : `example-${slug}`;
+        const block = await kbdbGetByPageName(env, pageName);
+        if (!block) {
+          return errorResponse(
+            "not_found",
+            `example "${slug}" 不存在`,
+            [
+              "call arcrun_list_examples() 看可用 slug",
+              "或 arcrun_search_examples(use_case) 用自然語言找",
+            ],
+          );
+        }
+
+        let description_md = "";
+        try {
+          const meta = block.metadata_json ? JSON.parse(block.metadata_json) : null;
+          description_md = meta?.description_md ?? "";
+        } catch {}
+
+        return successResponse({
+          slug,
+          page_name: block.page_name,
+          workflow_yaml: block.content,
+          description_md,
+          tags: parseTags(block.tags_json),
+        }, [
+          "拿 workflow_yaml 改成你自己的 → call arcrun_push_workflow",
+          "看 description_md 了解設計意圖 / 改造方向",
+        ]);
+      } catch (e) {
+        return errorResponse(
+          "fetch_failed",
+          e instanceof Error ? e.message : String(e),
+          ["稍後重試"],
+        );
+      }
+    },
+  );
+}
+
+export function registerSearchExamples(server: McpServer, env: Env) {
+  server.tool(
+    "arcrun_search_examples",
+    "用自然語言 use case 搜 workflow examples。回最相關 N 個。內部走 KBDB semantic search（embedding 比對）+ tag 過濾。",
+    {
+      query: z.string().min(3).describe("用 use case 描述，例如 '每天早上發 email 摘要' / 'RAG 從文件回答問題'"),
+      top_k: z.number().int().min(1).max(20).optional().describe("回幾個結果（預設 5）"),
+    },
+    async ({ query, top_k }) => {
+      try {
+        const k = top_k ?? 5;
+        // KBDB /search 是 unified semantic search（既有），filter type=workflow-example
+        const resp = await kbdbFetch(env, `/search`, {
+          method: "POST",
+          headers: { "Content-Type": "application/json" },
+          body: JSON.stringify({
+            query,
+            topK: k * 3,  // overfetch 後 filter type
+          }),
+        });
+
+        if (!resp.ok) {
+          return errorResponse(
+            "fetch_failed",
+            `KBDB search HTTP ${resp.status}`,
+            ["稍後重試", "改用 arcrun_list_examples(tag=...) 過濾"],
+            await resp.text().catch(() => ""),
+          );
+        }
+
+        const data = await resp.json<{ results?: Array<{ block?: KbdbBlock; score?: number }> }>();
+        const all = data.results ?? [];
+        const examples = all
+          .filter((r) => r.block?.type === "workflow-example")
+          .slice(0, k)
+          .map((r) => {
+            const b = r.block!;
+            return {
+              slug: b.page_name?.replace(/^example-/, "") ?? "",
+              page_name: b.page_name,
+              score: r.score,
+              tags: parseTags(b.tags_json),
+              preview: (b.content ?? "").slice(0, 200),
+            };
+          });
+
+        if (examples.length === 0) {
+          return successResponse(
+            { count: 0, examples: [], query },
+            [
+              "沒命中。可能 KBDB /search 還在等 embedding 建好（剛 sync 完要 1-5 分鐘）",
+              "改用 arcrun_list_examples(tag='...') 走 tag 過濾",
+              "或 arcrun_list_examples() 看全部清單自己挑",
+            ],
+          );
+        }
+
+        return successResponse(
+          { count: examples.length, examples, query },
+          [
+            "call arcrun_get_example(slug) 拿完整 YAML",
+            "score 高 = 跟你 query 更相關",
+          ],
+        );
+      } catch (e) {
+        return errorResponse(
+          "internal_error",
+          e instanceof Error ? e.message : String(e),
+          ["重試一次"],
+        );
+      }
+    },
+  );
+}
+
+export function registerAllSkillExampleTools(server: McpServer, env: Env) {
+  registerListSkills(server, env);
+  registerGetSkill(server, env);
+  registerListExamples(server, env);
+  registerGetExample(server, env);
+  registerSearchExamples(server, env);
+}

mcp/src/tools/arcrun_workflow_crud.ts

@@ -0,0 +1,379 @@
+/**
+ * Workflow CRUD tools — LI SDD M2.2
+ *
+ * 對應 .agents/specs/llm-interface/ Milestone 2.2。
+ *
+ * 取代既有 u6u_deploy_workflow（呼叫 /workflows/deploy — 該 endpoint 不存在，
+ * 是壞掉的 tool）+ u6u_list_workflows / u6u_get_workflow 透過 KBDB 撈 metadata
+ * 而非直接問 cypher-executor 的真實狀態。
+ *
+ * 新 tool 直打 cypher-executor /webhooks/named*：
+ *   - arcrun_push_workflow
+ *   - arcrun_list_workflows
+ *   - arcrun_get_workflow
+ *   - arcrun_delete_workflow
+ *   - arcrun_run_workflow
+ *
+ * 舊 u6u_* 待 M5 一次 rename + 退場（leo 2026-05-16 拍板）。在此之前，
+ * AI 看到兩套 tool — 用 arcrun_* 為主，u6u_* 有 deprecation hint。
+ */
+
+import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
+import { z } from "zod";
+import type { Env } from "../types.js";
+import { cypherFetch, errorResponse, successResponse } from "../lib/cypher-client.js";
+import { parse as parseYaml } from "yaml";
+
+const apiKeyDesc =
+  "你（用戶）的 arcrun api_key (ak_xxx)。從 https://arcrun.dev/me 取得";
+
+/**
+ * arcrun_push_workflow — 部署 YAML workflow
+ *
+ * 接受 yaml_content 或 graph object 兩種輸入。yaml_content 內部 parse 成 graph。
+ */
+export function registerPushWorkflow(server: McpServer, env: Env) {
+  server.tool(
+    "arcrun_push_workflow",
+    "部署 workflow 到 arcrun（取代 u6u_deploy_workflow，後者打不存在的 endpoint）。輸入可以是 YAML 字串或 graph 物件。**建議先 call arcrun_validate_yaml 確認 schema**。",
+    {
+      api_key: z.string().describe(apiKeyDesc),
+      yaml_content: z.string().optional().describe(
+        "YAML 字串。內部會 parse 成 {name, flow, config}。優先於 graph 參數"
+      ),
+      graph: z.unknown().optional().describe(
+        "已 parse 過的 graph 物件（含 nodes, edges）。yaml_content 沒給才用此"
+      ),
+      name: z.string().optional().describe(
+        "workflow 名稱（只能 [a-zA-Z0-9_-]）。若給 yaml_content 會從 yaml 抽 name 欄"
+      ),
+      description: z.string().optional().describe("workflow 描述（選填）"),
+    },
+    async ({ api_key, yaml_content, graph, name, description }) => {
+      let workflowName: string | undefined = name;
+      let workflowGraph: unknown = graph;
+      let workflowConfig: unknown = undefined;
+
+      // 如果有 yaml_content，parse 出 name + graph + config
+      if (yaml_content) {
+        try {
+          const parsed = parseYaml(yaml_content) as {
+            name?: string;
+            description?: string;
+            flow?: string[];
+            config?: Record<string, unknown>;
+            nodes?: unknown[];
+            edges?: unknown[];
+          };
+          workflowName = workflowName ?? parsed.name;
+          description = description ?? parsed.description;
+          workflowConfig = parsed.config;
+
+          // 若 yaml 是已展開的 {nodes, edges} 格式
+          if (parsed.nodes && parsed.edges) {
+            workflowGraph = { nodes: parsed.nodes, edges: parsed.edges };
+          }
+          // 若 yaml 是 cypher binding {flow, config} 格式，傳 raw 給 cypher-executor parse
+          else if (parsed.flow && parsed.config) {
+            workflowGraph = { flow: parsed.flow, config: parsed.config };
+          }
+        } catch (e) {
+          return errorResponse(
+            "validation_failed",
+            `YAML parse 失敗：${e instanceof Error ? e.message : String(e)}`,
+            ["檢查 YAML 縮排 / 引號 / 冒號", "用 yamllint 或 validator 先過一次"],
+          );
+        }
+      }
+
+      if (!workflowName) {
+        return errorResponse(
+          "validation_failed",
+          "缺少 workflow name（yaml_content 內 'name:' 欄或 name 參數）",
+          ["yaml 加 name: my_workflow 欄", "或直接傳 name 參數"],
+        );
+      }
+
+      if (!workflowGraph) {
+        return errorResponse(
+          "validation_failed",
+          "缺少 graph 資料（yaml_content 內 flow+config 或 nodes+edges，或直接傳 graph 參數）",
+          ["yaml 至少含 flow: + config: 兩欄", "或直接傳 graph 參數"],
+        );
+      }
+
+      try {
+        const res = await cypherFetch(env, "/webhooks/named", {
+          apiKey: api_key,
+          method: "POST",
+          body: {
+            name: workflowName,
+            graph: workflowGraph,
+            config: workflowConfig,
+            description,
+          },
+        });
+
+        const body = await res.json().catch(() => ({} as Record<string, unknown>));
+        if (!res.ok) {
+          return errorResponse(
+            "push_failed",
+            `部署失敗 HTTP ${res.status}: ${(body as { error?: string }).error ?? 'unknown'}`,
+            [
+              "先 call arcrun_validate_yaml 確認 graph schema 正確",
+              "確認 workflow name 符合 [a-zA-Z0-9_-] 格式",
+              "確認 api_key 是 ak_xxx 格式且有效",
+            ],
+            JSON.stringify(body),
+          );
+        }
+
+        const result = body as { name?: string; webhook_url?: string };
+        return successResponse(result, [
+          `部署成功！webhook URL: ${result.webhook_url}`,
+          `下一步：call arcrun_run_workflow('${result.name}', {你的 input}) 測試`,
+          "或對 webhook URL 直接 curl POST 觸發",
+        ]);
+      } catch (e) {
+        return errorResponse(
+          "internal_error",
+          e instanceof Error ? e.message : String(e),
+          ["重試一次"],
+        );
+      }
+    },
+  );
+}
+
+export function registerListWorkflows(server: McpServer, env: Env) {
+  server.tool(
+    "arcrun_list_workflows",
+    "列出你 (api_key 對應 namespace) 已部署的所有 workflow。回 [{name}]。",
+    {
+      api_key: z.string().describe(apiKeyDesc),
+    },
+    async ({ api_key }) => {
+      try {
+        const res = await cypherFetch(env, "/webhooks/named", {
+          apiKey: api_key,
+        });
+        const body = await res.json().catch(() => null);
+        if (!res.ok) {
+          return errorResponse(
+            "fetch_failed",
+            `撈 workflow 列表失敗 HTTP ${res.status}`,
+            ["確認 api_key 正確", "稍後重試"],
+            JSON.stringify(body),
+          );
+        }
+        const data = body as { workflows?: Array<{ name: string; webhook_url?: string }> };
+        return successResponse(data, [
+          `${data.workflows?.length ?? 0} 個 workflow`,
+          "call arcrun_get_workflow(name) 看單個細節",
+          "call arcrun_list_recent_executions(workflow_name) 看執行歷史",
+        ]);
+      } catch (e) {
+        return errorResponse(
+          "internal_error",
+          e instanceof Error ? e.message : String(e),
+          ["重試一次"],
+        );
+      }
+    },
+  );
+}
+
+export function registerGetWorkflow(server: McpServer, env: Env) {
+  server.tool(
+    "arcrun_get_workflow",
+    "看單一 workflow 的完整定義（graph + config）。",
+    {
+      api_key: z.string().describe(apiKeyDesc),
+      name: z.string().describe("workflow 名稱"),
+    },
+    async ({ api_key, name }) => {
+      try {
+        // cypher-executor 既有 /webhooks/named GET 只回 [{name}] 不含細節，
+        // 要走 KV 直接讀 — 目前沒有單個 workflow GET endpoint。
+        // workaround：撈 list 然後 client filter（M2.x 加 GET /webhooks/named/:name）
+        const res = await cypherFetch(env, "/webhooks/named", {
+          apiKey: api_key,
+        });
+        const body = await res.json().catch(() => null) as {
+          workflows?: Array<{ name: string; webhook_url?: string }>;
+        } | null;
+
+        if (!res.ok || !body?.workflows) {
+          return errorResponse(
+            "fetch_failed",
+            `撈 workflow 列表失敗`,
+            ["確認 api_key 正確"],
+            JSON.stringify(body),
+          );
+        }
+
+        const found = body.workflows.find((w) => w.name === name);
+        if (!found) {
+          return errorResponse(
+            "not_found",
+            `workflow "${name}" 不存在或不屬於你`,
+            [
+              "call arcrun_list_workflows 看你有什麼 workflow",
+              "確認名稱拼寫正確（注意大小寫）",
+            ],
+          );
+        }
+
+        return successResponse(
+          {
+            name: found.name,
+            webhook_url: found.webhook_url,
+            note: "目前 list endpoint 不回完整 graph，未來會加 GET /webhooks/named/:name",
+          },
+          [
+            "可 call arcrun_list_recent_executions 看執行歷史",
+            "可 call arcrun_run_workflow 觸發測試",
+          ],
+        );
+      } catch (e) {
+        return errorResponse(
+          "internal_error",
+          e instanceof Error ? e.message : String(e),
+          ["重試一次"],
+        );
+      }
+    },
+  );
+}
+
+export function registerDeleteWorkflow(server: McpServer, env: Env) {
+  server.tool(
+    "arcrun_delete_workflow",
+    "刪除 workflow。**不可逆，確認後再做**。會清掉對應 cron index 與 webhook URL。",
+    {
+      api_key: z.string().describe(apiKeyDesc),
+      name: z.string().describe("要刪的 workflow 名稱"),
+      confirm: z.literal(true).describe("必須傳 true 確認"),
+    },
+    async ({ api_key, name, confirm: _confirm }) => {
+      try {
+        const res = await cypherFetch(env, `/webhooks/named/${encodeURIComponent(name)}`, {
+          apiKey: api_key,
+          method: "DELETE",
+        });
+        const body = await res.json().catch(() => ({}));
+        if (!res.ok) {
+          return errorResponse(
+            res.status === 404 ? "not_found" : "delete_failed",
+            res.status === 404
+              ? `workflow "${name}" 不存在`
+              : `刪除失敗 HTTP ${res.status}`,
+            [
+              "call arcrun_list_workflows 確認名稱",
+              "若已不存在可忽略此錯誤",
+            ],
+            JSON.stringify(body),
+          );
+        }
+        return successResponse({ deleted: name }, [
+          `已刪除 ${name}`,
+          "若該 workflow 有 cron，索引也已清",
+        ]);
+      } catch (e) {
+        return errorResponse(
+          "internal_error",
+          e instanceof Error ? e.message : String(e),
+          ["重試一次"],
+        );
+      }
+    },
+  );
+}
+
+export function registerRunWorkflow(server: McpServer, env: Env) {
+  server.tool(
+    "arcrun_run_workflow",
+    "觸發 workflow 執行。input 物件帶進 trigger context。回 {success, data, trace?, duration_ms}。",
+    {
+      api_key: z.string().describe(apiKeyDesc),
+      name: z.string().describe("workflow 名稱"),
+      input: z.record(z.unknown()).optional().describe(
+        "trigger context（會塞進 workflow 第一個節點的輸入）。記得帶 api_key 給內部需要的節點用"
+      ),
+    },
+    async ({ api_key, name, input }) => {
+      try {
+        const triggerBody = input ?? {};
+        // 若 input 沒帶 api_key，自動補（內部多數零件需要）
+        if (!('api_key' in triggerBody)) {
+          (triggerBody as Record<string, unknown>).api_key = api_key;
+        }
+
+        const res = await cypherFetch(env, `/webhooks/named/${encodeURIComponent(name)}/trigger`, {
+          apiKey: api_key,
+          method: "POST",
+          body: triggerBody,
+        });
+        const body = await res.json().catch(() => null) as {
+          success?: boolean;
+          data?: unknown;
+          error?: string;
+          duration_ms?: number;
+          trace?: unknown;
+        } | null;
+
+        if (res.status === 404) {
+          return errorResponse(
+            "not_found",
+            `workflow "${name}" 不存在`,
+            ["call arcrun_list_workflows 確認名稱", "或先 arcrun_push_workflow 部署"],
+          );
+        }
+
+        // workflow 自己 success/fail 不算 HTTP 錯誤
+        const isPaused = body?.error && /workflow paused/i.test(body.error);
+        if (isPaused) {
+          return successResponse(
+            { ...body, status: "running_async" },
+            [
+              "workflow 已接受，正在背景跑（等 claude_api 等 daemon callback）",
+              "call arcrun_list_paused_executions 看當前 running_async 的",
+              "正常 30-90 秒會 resume 完成（從 user 角度像同步完成）",
+            ],
+          );
+        }
+
+        if (!body?.success) {
+          return errorResponse(
+            "execution_failed",
+            body?.error ?? `執行失敗 HTTP ${res.status}`,
+            [
+              "看 trace 陣列第一個 status=failed 的 node 是哪個",
+              "call arcrun_list_recent_executions 看歷史趨勢",
+            ],
+            JSON.stringify(body),
+          );
+        }
+
+        return successResponse(body, [
+          `執行成功，耗時 ${body.duration_ms}ms`,
+          "call arcrun_list_recent_executions 看歷史 verdict",
+        ]);
+      } catch (e) {
+        return errorResponse(
+          "internal_error",
+          e instanceof Error ? e.message : String(e),
+          ["重試一次"],
+        );
+      }
+    },
+  );
+}
+
+export function registerAllWorkflowCrudTools(server: McpServer, env: Env) {
+  registerPushWorkflow(server, env);
+  registerListWorkflows(server, env);
+  registerGetWorkflow(server, env);
+  registerDeleteWorkflow(server, env);
+  registerRunWorkflow(server, env);
+}

mcp/src/tools/registry.ts

@@ -0,0 +1,49 @@
+import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
+import { Env } from "../types.js";
+import { registerSearchComponents } from "./u6u_search_components.js";
+import { registerExecuteWorkflow } from "./u6u_execute_workflow.js";
+import { registerDeployWorkflow } from "./u6u_deploy_workflow.js";
+import { registerPublishComponent } from "./u6u_publish_component.js";
+import { registerListWorkflows } from "./u6u_list_workflows.js";
+import { registerGetWorkflow } from "./u6u_get_workflow.js";
+import { registerListComponents } from "./u6u_list_components.js";
+import { registerGetComponent } from "./u6u_get_component.js";
+import { registerGetComponentGuide } from "./u6u_get_component_guide.js";
+import { registerCreateTag } from "./u6u_create_tag.js";
+import { registerListTags } from "./u6u_list_tags.js";
+import { registerDeleteTag } from "./u6u_delete_tag.js";
+import { registerTagResource } from "./u6u_tag_resource.js";
+import { registerUntagResource } from "./u6u_untag_resource.js";
+import { registerGetGuiContext } from "./u6u_get_gui_context.js";
+import { registerReportFeedback } from "./arcrun_report_feedback.js";
+import { registerAllIntrospectionTools } from "./arcrun_introspection.js";
+import { registerAllWorkflowCrudTools } from "./arcrun_workflow_crud.js";
+import { registerAllSkillExampleTools } from "./arcrun_skills_examples.js";
+
+export function registerAllTools(server: McpServer, env: Env, orgNamespace: string, partnerToken: string) {
+  registerSearchComponents(server, env, orgNamespace);
+  registerExecuteWorkflow(server, env, orgNamespace, partnerToken);
+  registerDeployWorkflow(server, env, orgNamespace);
+  registerPublishComponent(server, env, orgNamespace);
+  registerListWorkflows(server, env, orgNamespace);
+  registerGetWorkflow(server, env, orgNamespace);
+  registerListComponents(server, env, orgNamespace);
+  registerGetComponent(server, env, orgNamespace);
+  registerGetComponentGuide(server, env, orgNamespace);
+  registerCreateTag(server, env, orgNamespace);
+  registerListTags(server, env, orgNamespace);
+  registerDeleteTag(server, env, orgNamespace);
+  registerTagResource(server, env, orgNamespace);
+  registerUntagResource(server, env, orgNamespace);
+  registerGetGuiContext(server, env, orgNamespace);
+  // LI SDD M1.3: explicit feedback tool (新命名規範 arcrun_*)
+  registerReportFeedback(server, env, orgNamespace);
+  // LI SDD M2.2: introspection tools (validate / paused / trace / recent executions)
+  registerAllIntrospectionTools(server, env);
+  // LI SDD M2.2: workflow CRUD (push / list / get / delete / run)
+  // 取代既有 u6u_deploy_workflow (打不存在的 /workflows/deploy endpoint)
+  registerAllWorkflowCrudTools(server, env);
+  // LI SDD M3.2: skills + examples lookup（KBDB-backed）
+  // 走 sync-registry-to-kbdb.py 把 registry/{skills,examples} 同步進 KBDB
+  registerAllSkillExampleTools(server, env);
+}

mcp/src/tools/u6u_create_tag.ts

@@ -0,0 +1,47 @@
+import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
+import { z } from "zod";
+import { Env } from "../types.js";
+import { kbdbFetch } from "../lib/kbdb-client.js";
+
+export function registerCreateTag(server: McpServer, env: Env, orgNamespace: string) {
+  server.tool(
+    "u6u_create_tag",
+    "在當前命名空間下建立新的 tag，用於分類工作流與零件。",
+    {
+      name: z.string().describe("Tag 名稱（在當前 org_namespace 下唯一）"),
+      description: z.string().optional().describe("Tag 描述（選填）")
+    },
+    async ({ name, description }) => {
+      try {
+        if (!env.KBDB) {
+          return { content: [{ type: "text", text: "Error: KBDB service binding unavailable" }], isError: true };
+        }
+        // Check for duplicate
+        const checkResp = await kbdbFetch(env, `/records/search?template=tag&user_id=${encodeURIComponent(orgNamespace)}&name=${encodeURIComponent(name)}`);
+        if (checkResp.ok) {
+          const checkData = await checkResp.json<{ records: unknown[] }>();
+          if (checkData.records && checkData.records.length > 0) {
+            return { content: [{ type: "text", text: `Error: Tag '${name}' already exists in this namespace` }], isError: true };
+          }
+        }
+        const recordId = `tag-${orgNamespace}-${name}`;
+        const createResp = await kbdbFetch(env, `/records`, {
+          method: "POST",
+          headers: { "Content-Type": "application/json" },
+          body: JSON.stringify({
+            template: "tag",
+            record_id: recordId,
+            user_id: orgNamespace,
+            values: { name, description: description ?? "", org_namespace: orgNamespace, created_at: new Date().toISOString() }
+          })
+        });
+        if (!createResp.ok) {
+          return { content: [{ type: "text", text: `Error creating tag: ${await createResp.text()}` }], isError: true };
+        }
+        return { content: [{ type: "text", text: JSON.stringify(await createResp.json(), null, 2) }] };
+      } catch (error) {
+        return { content: [{ type: "text", text: `Internal Error: ${error instanceof Error ? error.message : String(error)}` }], isError: true };
+      }
+    }
+  );
+}

mcp/src/tools/u6u_delete_tag.ts

@@ -0,0 +1,30 @@
+import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
+import { z } from "zod";
+import { Env } from "../types.js";
+import { kbdbFetch } from "../lib/kbdb-client.js";
+
+export function registerDeleteTag(server: McpServer, env: Env, orgNamespace: string) {
+  server.tool(
+    "u6u_delete_tag",
+    "刪除當前命名空間下的指定 tag。",
+    { tag_name: z.string().describe("要刪除的 Tag 名稱") },
+    async ({ tag_name }) => {
+      try {
+        if (!env.KBDB) {
+          return { content: [{ type: "text", text: "Error: KBDB service binding unavailable" }], isError: true };
+        }
+        const recordId = `tag-${orgNamespace}-${tag_name}`;
+        const deleteResp = await kbdbFetch(env, `/records/${encodeURIComponent(recordId)}`, { method: "DELETE" });
+        if (deleteResp.status === 404) {
+          return { content: [{ type: "text", text: `Error: Tag '${tag_name}' not found` }], isError: true };
+        }
+        if (!deleteResp.ok) {
+          return { content: [{ type: "text", text: `Error deleting tag: ${await deleteResp.text()}` }], isError: true };
+        }
+        return { content: [{ type: "text", text: `Tag '${tag_name}' deleted successfully` }] };
+      } catch (error) {
+        return { content: [{ type: "text", text: `Internal Error: ${error instanceof Error ? error.message : String(error)}` }], isError: true };
+      }
+    }
+  );
+}

mcp/src/tools/u6u_deploy_workflow.ts

@@ -0,0 +1,81 @@
+import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
+import { z } from "zod";
+import { Env } from "../types.js";
+import { kbdbFetch } from "../lib/kbdb-client.js";
+
+export function registerDeployWorkflow(server: McpServer, env: Env, orgNamespace: string) {
+  server.tool(
+    "u6u_deploy_workflow",
+    "將工作流 YAML 配置正式部署至雲端引擎，完成註冊與排程設定。",
+    {
+      yaml_content: z.string().describe("工作流的 YAML 配置內容")
+    },
+    async ({ yaml_content }) => {
+      try {
+        if (!env.CYPHER_EXECUTOR) {
+          return {
+            content: [{ type: "text", text: "Error: CYPHER_EXECUTOR service binding is not configured." }],
+            isError: true
+          };
+        }
+
+        const response = await env.CYPHER_EXECUTOR.fetch("http://cypher-executor/workflows/deploy", {
+          method: "POST",
+          headers: { "Content-Type": "application/yaml" },
+          body: yaml_content
+        });
+
+        if (!response.ok) {
+          const errorText = await response.text();
+          return {
+            content: [{ type: "text", text: `Deployment failed: ${errorText}` }],
+            isError: true
+          };
+        }
+
+        const result = await response.json<{ workflow_id?: string; [key: string]: unknown }>();
+        const workflowId = result.workflow_id ?? crypto.randomUUID();
+
+        // Parse workflow name from YAML
+        const nameMatch = yaml_content.match(/^name:\s*(.+)$/m);
+        const workflowName = nameMatch ? nameMatch[1].trim() : workflowId;
+
+        // Store workflow metadata in KBDB
+        if (env.KBDB) {
+          const kbdbResp = await kbdbFetch(env, "/records", {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({
+              template: "workflow_metadata",
+              record_id: `wf-${workflowId}`,
+              user_id: orgNamespace,
+              values: {
+                workflow_id: workflowId,
+                name: workflowName,
+                deployed_at: new Date().toISOString(),
+                org_namespace: orgNamespace
+              }
+            })
+          });
+
+          if (!kbdbResp.ok) {
+            const errText = await kbdbResp.text();
+            return {
+              content: [{ type: "text", text: `Deployment succeeded but failed to store metadata: ${errText}` }],
+              isError: true
+            };
+          }
+        }
+
+        return {
+          content: [{ type: "text", text: `Successfully deployed workflow: ${JSON.stringify(result, null, 2)}` }]
+        };
+      } catch (error) {
+        return {
+          content: [{ type: "text", text: `Internal Error: ${error instanceof Error ? error.message : String(error)}` }],
+          isError: true
+        };
+      }
+    }
+  );
+}

mcp/src/tools/u6u_execute_workflow.ts

@@ -0,0 +1,54 @@
+import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
+import { z } from "zod";
+import { Env } from "../types.js";
+
+export function registerExecuteWorkflow(server: McpServer, env: Env, orgNamespace: string, partnerToken: string) {
+  server.tool(
+    "u6u_execute_workflow",
+    "在沙盒環境中即時執行工作流，驗證 triplets 邏輯是否正確。每個 config 鍵對應 triplets 中的節點名，內含 component(零件 canonical_id)、recipe(prompt_recipe:xxx，選用)、與該節點的其他靜態參數。",
+    {
+      triplets: z.array(z.string()).describe("工作流三元組，例：['input >> 完成後 >> synth']"),
+      context: z.record(z.string(), z.any()).describe("初始變數（測試資料 / 上游節點輸出模擬）"),
+      config: z.record(z.string(), z.record(z.string(), z.any())).optional().describe("每節點配置：{ node_name: { component, recipe?, ...params } }")
+    },
+    async ({ triplets, context, config }) => {
+      try {
+        if (!env.CYPHER_EXECUTOR) {
+          return {
+            content: [{ type: "text", text: "Error: CYPHER_EXECUTOR service binding is not configured." }],
+            isError: true
+          };
+        }
+
+        // KI-12 修：改打 /cypher/execute（吃 triplets+config），原 /execute 是吃完整 graph 的舊路徑
+        // KI-15 修：轉發 partner token 給 cypher-executor，讓 recipe expander 能用 ak_ key 抓 KBDB
+        const response = await env.CYPHER_EXECUTOR.fetch("http://cypher-executor/cypher/execute", {
+          method: "POST",
+          headers: {
+            "Content-Type": "application/json",
+            "X-Arcrun-API-Key": partnerToken
+          },
+          body: JSON.stringify({ triplets, context, config })
+        });
+
+        if (!response.ok) {
+          const errorText = await response.text();
+          return {
+            content: [{ type: "text", text: `Execution failed: ${errorText}` }],
+            isError: true
+          };
+        }
+
+        const result = await response.json();
+        return {
+          content: [{ type: "text", text: JSON.stringify(result, null, 2) }]
+        };
+      } catch (error) {
+        return {
+          content: [{ type: "text", text: `Internal Error: ${error instanceof Error ? error.message : String(error)}` }],
+          isError: true
+        };
+      }
+    }
+  );
+}

mcp/src/tools/u6u_get_component.ts

@@ -0,0 +1,59 @@
+import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
+import { z } from "zod";
+import { Env } from "../types.js";
+
+/**
+ * u6u_get_component — 取得零件完整合約
+ * 呼叫 Component Registry GET /components/:id
+ */
+export function registerGetComponent(server: McpServer, env: Env, orgNamespace: string) {
+  server.tool(
+    "u6u_get_component",
+    "取得指定零件的完整合約，包含 canonical_id、display_name、category、version、stability、input_schema、output_schema、gherkin_tests、評分統計等。",
+    {
+      canonical_id: z.string().describe("零件 canonical_id（如 validate_json）"),
+    },
+    async ({ canonical_id }) => {
+      try {
+        if (!env.COMPONENT_REGISTRY) {
+          return {
+            content: [{ type: "text", text: "Error: COMPONENT_REGISTRY service binding is not configured." }],
+            isError: true,
+          };
+        }
+
+        const response = await env.COMPONENT_REGISTRY.fetch(
+          `http://component-registry/components/${encodeURIComponent(canonical_id)}`,
+          { method: "GET" },
+        );
+
+        if (response.status === 404) {
+          return {
+            content: [{ type: "text", text: `零件 '${canonical_id}' 不存在。可用 u6u_search_components 搜尋相似零件。` }],
+            isError: true,
+          };
+        }
+
+        if (!response.ok) {
+          return {
+            content: [{ type: "text", text: `Error: ${await response.text()}` }],
+            isError: true,
+          };
+        }
+
+        const result = await response.json() as { data?: unknown };
+        return {
+          content: [{
+            type: "text",
+            text: JSON.stringify(result.data ?? result, null, 2),
+          }],
+        };
+      } catch (error) {
+        return {
+          content: [{ type: "text", text: `Internal Error: ${error instanceof Error ? error.message : String(error)}` }],
+          isError: true,
+        };
+      }
+    }
+  );
+}

mcp/src/tools/u6u_get_component_guide.ts

@@ -0,0 +1,47 @@
+import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
+import { Env } from "../types.js";
+
+/**
+ * u6u_get_component_guide — 取得零件開發指引
+ * 呼叫 Component Registry GET /components/guide
+ * AI 在開發新零件前應先讀取此指引
+ */
+export function registerGetComponentGuide(server: McpServer, env: Env, orgNamespace: string) {
+  server.tool(
+    "u6u_get_component_guide",
+    "取得 u6u 零件開發指引（Markdown 格式）。包含 TinyGo 白名單 import、禁止行為、component.contract.yaml 完整範例、本地測試指令。開發新零件前必須先讀取此指引。",
+    {},
+    async () => {
+      try {
+        if (!env.COMPONENT_REGISTRY) {
+          return {
+            content: [{ type: "text", text: "Error: COMPONENT_REGISTRY service binding is not configured." }],
+            isError: true,
+          };
+        }
+
+        const response = await env.COMPONENT_REGISTRY.fetch(
+          "http://component-registry/components/guide",
+          { method: "GET" },
+        );
+
+        if (!response.ok) {
+          return {
+            content: [{ type: "text", text: `Error fetching guide: ${await response.text()}` }],
+            isError: true,
+          };
+        }
+
+        const guide = await response.text();
+        return {
+          content: [{ type: "text", text: guide }],
+        };
+      } catch (error) {
+        return {
+          content: [{ type: "text", text: `Internal Error: ${error instanceof Error ? error.message : String(error)}` }],
+          isError: true,
+        };
+      }
+    }
+  );
+}

mcp/src/tools/u6u_get_gui_context.ts

@@ -0,0 +1,84 @@
+import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
+import { z } from "zod";
+import { Env } from "../types.js";
+import { kbdbFetch } from "../lib/kbdb-client.js";
+
+interface ActionLogSlots {
+  org_namespace?: string;
+  action_type?: string;
+  payload?: string;
+  occurred_at?: string;
+}
+
+interface ActionLogRecord {
+  id: string;
+  slots?: ActionLogSlots;
+}
+
+export function registerGetGuiContext(server: McpServer, env: Env, orgNamespace: string) {
+  server.tool(
+    "u6u_get_gui_context",
+    "查詢用戶在 GUI 上的最近操作記錄，了解用戶的當前意圖與操作上下文。" +
+    "回傳最近 N 條操作記錄（從新到舊），以及用戶當前所在頁面和正在編輯的 Workflow ID。",
+    {
+      limit: z.number().int().min(1).max(100).default(20)
+        .describe("要取回的最近操作數量（預設 20，最大 100）"),
+    },
+    async ({ limit }) => {
+      try {
+        if (!env.KBDB) {
+          return {
+            content: [{ type: "text", text: "Error: KBDB service binding unavailable" }],
+            isError: true,
+          };
+        }
+
+        const resp = await kbdbFetch(
+          env,
+          `/records/search?template_id=tpl-action-log&user_id=${encodeURIComponent(orgNamespace)}&limit=${limit ?? 20}`
+        );
+
+        if (!resp.ok) {
+          return {
+            content: [{ type: "text", text: `Error querying action log: ${await resp.text()}` }],
+            isError: true,
+          };
+        }
+
+        const data = await resp.json<{ records: ActionLogRecord[] }>();
+        const records = data.records ?? [];
+
+        // 按 occurred_at 降序排列（最新在前）
+        const sorted = records
+          .map(r => ({
+            action_type: r.slots?.action_type ?? '',
+            payload: (() => {
+              try { return JSON.parse(r.slots?.payload ?? '{}'); } catch { return {}; }
+            })(),
+            occurred_at: r.slots?.occurred_at ?? '',
+          }))
+          .sort((a, b) => b.occurred_at.localeCompare(a.occurred_at))
+          .slice(0, limit ?? 20);
+
+        // 提取當前頁面和正在操作的 Workflow
+        const lastNavigate = sorted.find(a => a.action_type === 'NAVIGATE');
+        const lastOpenWorkflow = sorted.find(a => a.action_type === 'OPEN_WORKFLOW');
+
+        const context = {
+          recent_actions: sorted,
+          current_page: (lastNavigate?.payload as { page?: string })?.page ?? null,
+          open_workflow_id: (lastOpenWorkflow?.payload as { workflow_id?: string })?.workflow_id ?? null,
+        };
+
+        return {
+          content: [{ type: "text", text: JSON.stringify(context, null, 2) }],
+        };
+      } catch (error) {
+        return {
+          content: [{ type: "text", text: `Internal Error: ${error instanceof Error ? error.message : String(error)}` }],
+          isError: true,
+        };
+      }
+    }
+  );
+}

mcp/src/tools/u6u_get_workflow.ts

@@ -0,0 +1,33 @@
+import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
+import { z } from "zod";
+import { Env } from "../types.js";
+import { kbdbFetch } from "../lib/kbdb-client.js";
+
+export function registerGetWorkflow(server: McpServer, env: Env, orgNamespace: string) {
+  server.tool(
+    "u6u_get_workflow",
+    "取得指定工作流的 metadata，包含名稱、部署時間與 tag 列表。",
+    { workflow_id: z.string().describe("工作流 ID") },
+    async ({ workflow_id }) => {
+      try {
+        if (!env.KBDB) {
+          return { content: [{ type: "text", text: "Error: KBDB service binding unavailable" }], isError: true };
+        }
+        const resp = await kbdbFetch(env, `/records/wf-${encodeURIComponent(workflow_id)}`);
+        if (resp.status === 404) {
+          return { content: [{ type: "text", text: `Error: Workflow '${workflow_id}' not found` }], isError: true };
+        }
+        if (!resp.ok) {
+          return { content: [{ type: "text", text: `Error querying workflow: ${await resp.text()}` }], isError: true };
+        }
+        const record = await resp.json<{ slots: { workflow_id: string; name: string; deployed_at: string; org_namespace: string } }>();
+        if (record.slots.org_namespace !== orgNamespace) {
+          return { content: [{ type: "text", text: `Error: Workflow '${workflow_id}' not found` }], isError: true };
+        }
+        return { content: [{ type: "text", text: JSON.stringify(record.slots, null, 2) }] };
+      } catch (error) {
+        return { content: [{ type: "text", text: `Internal Error: ${error instanceof Error ? error.message : String(error)}` }], isError: true };
+      }
+    }
+  );
+}

mcp/src/tools/u6u_list_components.ts

@@ -0,0 +1,39 @@
+import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
+import { z } from "zod";
+import { Env } from "../types.js";
+import { kbdbFetch } from "../lib/kbdb-client.js";
+
+export function registerListComponents(server: McpServer, env: Env, orgNamespace: string) {
+  server.tool(
+    "u6u_list_components",
+    "列出當前命名空間下所有已發佈的零件，可選擇按 tag 篩選。",
+    { tag: z.string().optional().describe("按 tag 名稱篩選（選填）") },
+    async ({ tag }) => {
+      try {
+        if (!env.KBDB) {
+          return { content: [{ type: "text", text: "Error: KBDB service binding unavailable" }], isError: true };
+        }
+        let componentIds: string[] | null = null;
+        if (tag) {
+          const tagResp = await kbdbFetch(env, `/records/search?template=resource_tag&user_id=${encodeURIComponent(orgNamespace)}&tag_name=${encodeURIComponent(tag)}&resource_type=component`);
+          if (!tagResp.ok) {
+            return { content: [{ type: "text", text: `Error querying tags: ${await tagResp.text()}` }], isError: true };
+          }
+          const tagData = await tagResp.json<{ records: Array<{ slots: { resource_id: string } }> }>();
+          componentIds = tagData.records.map(r => r.slots.resource_id);
+          if (componentIds.length === 0) return { content: [{ type: "text", text: JSON.stringify([], null, 2) }] };
+        }
+        const resp = await kbdbFetch(env, `/records/search?template=component_metadata&user_id=${encodeURIComponent(orgNamespace)}`);
+        if (!resp.ok) {
+          return { content: [{ type: "text", text: `Error querying components: ${await resp.text()}` }], isError: true };
+        }
+        const data = await resp.json<{ records: Array<{ slots: { component_id: string; name: string; published_at: string; org_namespace: string } }> }>();
+        let components = data.records.map(r => r.slots);
+        if (componentIds !== null) components = components.filter(c => componentIds!.includes(c.component_id));
+        return { content: [{ type: "text", text: JSON.stringify(components, null, 2) }] };
+      } catch (error) {
+        return { content: [{ type: "text", text: `Internal Error: ${error instanceof Error ? error.message : String(error)}` }], isError: true };
+      }
+    }
+  );
+}

mcp/src/tools/u6u_list_tags.ts

@@ -0,0 +1,26 @@
+import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
+import { Env } from "../types.js";
+import { kbdbFetch } from "../lib/kbdb-client.js";
+
+export function registerListTags(server: McpServer, env: Env, orgNamespace: string) {
+  server.tool(
+    "u6u_list_tags",
+    "列出當前命名空間下所有的 tag。",
+    {},
+    async () => {
+      try {
+        if (!env.KBDB) {
+          return { content: [{ type: "text", text: "Error: KBDB service binding unavailable" }], isError: true };
+        }
+        const resp = await kbdbFetch(env, `/records/search?template=tag&user_id=${encodeURIComponent(orgNamespace)}`);
+        if (!resp.ok) {
+          return { content: [{ type: "text", text: `Error fetching tags: ${await resp.text()}` }], isError: true };
+        }
+        const data = await resp.json<{ records: unknown[] }>();
+        return { content: [{ type: "text", text: JSON.stringify(data.records, null, 2) }] };
+      } catch (error) {
+        return { content: [{ type: "text", text: `Internal Error: ${error instanceof Error ? error.message : String(error)}` }], isError: true };
+      }
+    }
+  );
+}

mcp/src/tools/u6u_list_workflows.ts

@@ -0,0 +1,39 @@
+import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
+import { z } from "zod";
+import { Env } from "../types.js";
+import { kbdbFetch } from "../lib/kbdb-client.js";
+
+export function registerListWorkflows(server: McpServer, env: Env, orgNamespace: string) {
+  server.tool(
+    "u6u_list_workflows",
+    "列出當前命名空間下所有已部署的工作流，可選擇按 tag 篩選。",
+    { tag: z.string().optional().describe("按 tag 名稱篩選（選填）") },
+    async ({ tag }) => {
+      try {
+        if (!env.KBDB) {
+          return { content: [{ type: "text", text: "Error: KBDB service binding unavailable" }], isError: true };
+        }
+        let workflowIds: string[] | null = null;
+        if (tag) {
+          const tagResp = await kbdbFetch(env, `/records/search?template=resource_tag&user_id=${encodeURIComponent(orgNamespace)}&tag_name=${encodeURIComponent(tag)}&resource_type=workflow`);
+          if (!tagResp.ok) {
+            return { content: [{ type: "text", text: `Error querying tags: ${await tagResp.text()}` }], isError: true };
+          }
+          const tagData = await tagResp.json<{ records: Array<{ slots: { resource_id: string } }> }>();
+          workflowIds = tagData.records.map(r => r.slots.resource_id);
+          if (workflowIds.length === 0) return { content: [{ type: "text", text: JSON.stringify([], null, 2) }] };
+        }
+        const resp = await kbdbFetch(env, `/records/search?template=workflow_metadata&user_id=${encodeURIComponent(orgNamespace)}`);
+        if (!resp.ok) {
+          return { content: [{ type: "text", text: `Error querying workflows: ${await resp.text()}` }], isError: true };
+        }
+        const data = await resp.json<{ records: Array<{ slots: { workflow_id: string; name: string; deployed_at: string; org_namespace: string } }> }>();
+        let workflows = data.records.map(r => r.slots);
+        if (workflowIds !== null) workflows = workflows.filter(w => workflowIds!.includes(w.workflow_id));
+        return { content: [{ type: "text", text: JSON.stringify(workflows, null, 2) }] };
+      } catch (error) {
+        return { content: [{ type: "text", text: `Internal Error: ${error instanceof Error ? error.message : String(error)}` }], isError: true };
+      }
+    }
+  );
+}

mcp/src/tools/u6u_publish_component.ts

@@ -0,0 +1,83 @@
+import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
+import { z } from "zod";
+import { Env } from "../types.js";
+
+/**
+ * u6u_publish_component — 提交 TinyGo WASM 零件至 Component Registry
+ *
+ * AI 工作流：
+ * 1. 先呼叫 u6u_get_component_guide 取得開發指引
+ * 2. 依指引用 TinyGo 撰寫零件（stdin/stdout JSON I/O）
+ * 3. 編譯為 .wasm，base64 編碼後提交
+ * 4. Registry 自動執行沙盒驗收（體積、syscall 掃描、Gherkin 測試）
+ */
+export function registerPublishComponent(server: McpServer, env: Env, orgNamespace: string) {
+  server.tool(
+    "u6u_publish_component",
+    "提交 TinyGo WASM 零件至 Component Registry。需提供 component.contract.yaml 內容與編譯後的 .wasm base64。提交前請先呼叫 u6u_get_component_guide 取得開發規範。",
+    {
+      contract: z.object({
+        canonical_id: z.string().describe("零件功能名稱（小寫底線，如 validate_json）"),
+        display_name: z.string().describe("顯示名稱（可自由命名）"),
+        category: z.enum(["logic", "api", "ui", "style", "anim"]).describe("零件分類"),
+        version: z.string().describe("版本（格式 vN，如 v1）"),
+        wasi_target: z.literal("preview1"),
+        stability: z.enum(["floating", "stable", "pinned"]).default("floating"),
+        runtime_compat: z.array(z.string()).describe("相容 runtime，如 [\"cf-workers\",\"wazero\"]"),
+        constraints: z.object({
+          max_size_kb: z.number().default(2048),
+          max_cold_start_ms: z.number().default(50),
+          no_network_syscall: z.boolean().default(true),
+          io_model: z.literal("stdin_stdout_json"),
+        }),
+        input_schema: z.record(z.unknown()).describe("JSON Schema"),
+        output_schema: z.record(z.unknown()).describe("JSON Schema"),
+        gherkin_tests: z.array(z.object({
+          scenario: z.string(),
+          given: z.string().describe("JSON 字串"),
+          then_contains: z.string().describe("預期輸出包含的字串"),
+        })).min(2).describe("至少一個 happy path 和一個 error path"),
+        description: z.string().optional(),
+        tags: z.array(z.string()).optional(),
+      }).describe("component.contract.yaml 內容"),
+      wasm_base64: z.string().describe("編譯後的 .wasm 檔案 base64 編碼"),
+    },
+    async ({ contract, wasm_base64 }) => {
+      try {
+        if (!env.COMPONENT_REGISTRY) {
+          return {
+            content: [{ type: "text", text: "Error: COMPONENT_REGISTRY service binding is not configured." }],
+            isError: true,
+          };
+        }
+
+        const response = await env.COMPONENT_REGISTRY.fetch("http://component-registry/components", {
+          method: "POST",
+          headers: { "Content-Type": "application/json" },
+          body: JSON.stringify({ contract, wasm_base64 }),
+        });
+
+        if (!response.ok) {
+          const errorText = await response.text();
+          return {
+            content: [{ type: "text", text: `Publish failed: ${errorText}` }],
+            isError: true,
+          };
+        }
+
+        const result = await response.json() as Record<string, unknown>;
+        return {
+          content: [{
+            type: "text",
+            text: `零件 ${contract.canonical_id} v${contract.version} 提交成功：\n${JSON.stringify(result, null, 2)}`,
+          }],
+        };
+      } catch (error) {
+        return {
+          content: [{ type: "text", text: `Internal Error: ${error instanceof Error ? error.message : String(error)}` }],
+          isError: true,
+        };
+      }
+    }
+  );
+}

mcp/src/tools/u6u_search_components.ts

@@ -0,0 +1,65 @@
+import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
+import { z } from "zod";
+import { Env } from "../types.js";
+
+/**
+ * u6u_search_components — 語意搜尋零件庫
+ * 呼叫 Component Registry GET /components/search?q=...
+ */
+export function registerSearchComponents(server: McpServer, env: Env, orgNamespace: string) {
+  server.tool(
+    "u6u_search_components",
+    "用自然語言語意搜尋零件庫，找出符合需求的零件。例如：「查詢 Google Sheets 資料」、「發送 LINE 訊息」、「驗證 JSON 格式」。回傳零件清單含 canonical_id、描述、評分。",
+    {
+      query: z.string().describe("自然語言搜尋詞，如「查詢 Google Sheets 資料」"),
+    },
+    async ({ query }) => {
+      try {
+        if (!env.COMPONENT_REGISTRY) {
+          return {
+            content: [{ type: "text", text: "Error: COMPONENT_REGISTRY service binding is not configured." }],
+            isError: true,
+          };
+        }
+
+        const response = await env.COMPONENT_REGISTRY.fetch(
+          `http://component-registry/components/search?q=${encodeURIComponent(query)}`,
+          { method: "GET", headers: { "Content-Type": "application/json" } },
+        );
+
+        if (!response.ok) {
+          const errorText = await response.text();
+          return {
+            content: [{ type: "text", text: `Search failed: ${errorText}` }],
+            isError: true,
+          };
+        }
+
+        const result = await response.json() as { data?: { results?: unknown[]; count?: number } };
+        const results = result.data?.results ?? [];
+        const count = result.data?.count ?? 0;
+
+        if (count === 0) {
+          return {
+            content: [{
+              type: "text",
+              text: `找不到符合「${query}」的零件。可以用 u6u_publish_component 提交新零件。`,
+            }],
+          };
+        }
+
+        return {
+          content: [{
+            type: "text",
+            text: `找到 ${count} 個零件：\n${JSON.stringify(results, null, 2)}`,
+          }],
+        };
+      } catch (error) {
+        return {
+          content: [{ type: "text", text: `Internal Error: ${error instanceof Error ? error.message : String(error)}` }],
+          isError: true,
+        };
+      }
+    }
+  );
+}

mcp/src/tools/u6u_tag_resource.ts

@@ -0,0 +1,57 @@
+import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
+import { z } from "zod";
+import { Env } from "../types.js";
+import { kbdbFetch } from "../lib/kbdb-client.js";
+
+export function registerTagResource(server: McpServer, env: Env, orgNamespace: string) {
+  server.tool(
+    "u6u_tag_resource",
+    "為當前命名空間下的工作流或零件加上 tag 標籤。",
+    {
+      resource_type: z.enum(["workflow", "component"]).describe("資源類型：workflow 或 component"),
+      resource_id: z.string().describe("資源 ID"),
+      tag_name: z.string().describe("要套用的 tag 名稱")
+    },
+    async ({ resource_type, resource_id, tag_name }) => {
+      try {
+        if (!env.KBDB) {
+          return { content: [{ type: "text", text: "Error: KBDB service binding unavailable" }], isError: true };
+        }
+        const tagResp = await kbdbFetch(env, `/records/search?template=tag&user_id=${encodeURIComponent(orgNamespace)}&name=${encodeURIComponent(tag_name)}`);
+        if (!tagResp.ok) {
+          return { content: [{ type: "text", text: "Error: KBDB service unavailable" }], isError: true };
+        }
+        const tagData = await tagResp.json<{ records: unknown[] }>();
+        if (!tagData.records || tagData.records.length === 0) {
+          return { content: [{ type: "text", text: `Error: Tag not found` }], isError: true };
+        }
+        const prefix = resource_type === "workflow" ? "wf" : "comp";
+        const resourceResp = await kbdbFetch(env, `/records/${prefix}-${resource_id}`);
+        if (!resourceResp.ok) {
+          return { content: [{ type: "text", text: `Error: Resource not found` }], isError: true };
+        }
+        const resourceData = await resourceResp.json<{ slots: { org_namespace: string } }>();
+        if (!resourceData.slots || resourceData.slots.org_namespace !== orgNamespace) {
+          return { content: [{ type: "text", text: `Error: Resource not found` }], isError: true };
+        }
+        const recordId = `rt-${resource_type}-${resource_id}-${tag_name}`;
+        const createResp = await kbdbFetch(env, `/records`, {
+          method: "POST",
+          headers: { "Content-Type": "application/json" },
+          body: JSON.stringify({
+            template: "resource_tag",
+            record_id: recordId,
+            user_id: orgNamespace,
+            values: { resource_type, resource_id, tag_name, org_namespace: orgNamespace }
+          })
+        });
+        if (!createResp.ok) {
+          return { content: [{ type: "text", text: `Error creating resource_tag: ${await createResp.text()}` }], isError: true };
+        }
+        return { content: [{ type: "text", text: JSON.stringify(await createResp.json(), null, 2) }] };
+      } catch (error) {
+        return { content: [{ type: "text", text: `Internal Error: ${error instanceof Error ? error.message : String(error)}` }], isError: true };
+      }
+    }
+  );
+}

mcp/src/tools/u6u_untag_resource.ts

@@ -0,0 +1,42 @@
+import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
+import { z } from "zod";
+import { Env } from "../types.js";
+import { kbdbFetch } from "../lib/kbdb-client.js";
+
+export function registerUntagResource(server: McpServer, env: Env, orgNamespace: string) {
+  server.tool(
+    "u6u_untag_resource",
+    "移除當前命名空間下工作流或零件的 tag 標籤。",
+    {
+      resource_type: z.enum(["workflow", "component"]).describe("資源類型：workflow 或 component"),
+      resource_id: z.string().describe("資源 ID"),
+      tag_name: z.string().describe("要移除的 tag 名稱")
+    },
+    async ({ resource_type, resource_id, tag_name }) => {
+      try {
+        if (!env.KBDB) {
+          return { content: [{ type: "text", text: "Error: KBDB service binding unavailable" }], isError: true };
+        }
+        const recordId = `rt-${resource_type}-${resource_id}-${tag_name}`;
+        const getResp = await kbdbFetch(env, `/records/${recordId}`);
+        if (getResp.status === 404) {
+          return { content: [{ type: "text", text: "Error: Resource tag association not found" }], isError: true };
+        }
+        if (!getResp.ok) {
+          return { content: [{ type: "text", text: "Error: KBDB service unavailable" }], isError: true };
+        }
+        const record = await getResp.json<{ slots: { org_namespace: string } }>();
+        if (!record.slots || record.slots.org_namespace !== orgNamespace) {
+          return { content: [{ type: "text", text: "Error: Resource tag association not found" }], isError: true };
+        }
+        const deleteResp = await kbdbFetch(env, `/records/${recordId}`, { method: "DELETE" });
+        if (!deleteResp.ok) {
+          return { content: [{ type: "text", text: "Error: KBDB service unavailable" }], isError: true };
+        }
+        return { content: [{ type: "text", text: `Tag '${tag_name}' removed from ${resource_type} '${resource_id}' successfully` }] };
+      } catch (error) {
+        return { content: [{ type: "text", text: `Internal Error: ${error instanceof Error ? error.message : String(error)}` }], isError: true };
+      }
+    }
+  );
+}