934b9265d9
按 issue 分段標明(檔 #5/#8 改動交疊處無法乾淨拆檔,故併一個 commit): #4 thin-shell §3.1 自力救濟階梯 + code-node 規則(純文檔/規則,code-node 零件未實作) #5 KBDB source filter(json_extract metadata_json 零建表)+ 能力對照;documents 聚合與 DELETE proxy 部分擱置等頂層 T8 #7 base embed 模組(kbdb/src/embed.ts)+ vectorize 開關(deploy/config/wrangler.toml 註解範本) + 語義查詢降級閉環(mode=semantic 未開→LIKE+capability_hint) #8 部分(workflow-discovery): - KBDB /entries/search 加 base 通用 entry_type filter(entry-crud/embed/route/kbdb-proxy 透傳) - /webhooks/named 強制 description(空→400,訊息要求操盤 AI 據實寫一句) - 部署雙寫 entry_type=workflow embeddable entry(waitUntil 非阻塞,供 search) - cypher GET /workflows/search + MCP u6u_search_workflows(優先語意、降級 hint) - cypher POST /workflows/backfill-search-entries(無 desc 列出不編造) - GET /webhooks/named 補回 description/created_at 欄位(為 list 來源收斂備) ⚠️ tsc 綠 = code done,非完成(mindset §7 禁假綠): - #7/#8 端到端待 leo21c 部署驗(Vectorize 需官方憑證、CC 跑不了) - #8 ①-a(MCP deploy 改打 /webhooks/named)未做、MCP deploy 那半仍 404 - #8 端到端(強制填擋空/語義命中/租戶隔離/降級 hint)未驗 Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
87 lines
3.4 KiB
TypeScript
87 lines
3.4 KiB
TypeScript
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
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import { z } from "zod";
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import { Env } from "../types.js";
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/**
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* u6u_search_workflows — 用自然語言找現成工作流(workflow-discovery R2)
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*
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* 北極星入口:AI 先查「有沒有現成工作流能做這件事」→ 找到就執行,別重造。
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* 呼叫 cypher GET /workflows/search → 轉發 KBDB /entries/search(entry_type=workflow + 本租戶)。
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* 優先語意搜尋;KBDB 未開 Vectorize → 自動降級關鍵字 + 回 capability_hint(不假裝語義)。
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*
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* 薄殼(rule 07):只做參數轉換 + 呼叫 + 格式化,零業務邏輯。形態對齊 u6u_search_components。
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* flag 安全:AI 收到意圖時主動 call 一次,無輪詢/排程。
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*/
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export function registerSearchWorkflows(
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server: McpServer,
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env: Env,
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orgNamespace: string,
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partnerToken: string,
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) {
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server.tool(
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"u6u_search_workflows",
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"用自然語言找現成的工作流(先查有沒有現成的能做這件事,找到就用,別重造)。例如:「把資料寫進 Google Sheets」、「每天抓 RSS 發通知」、「webhook 轉發到別的 API」。回傳本帳號下符合的工作流清單。",
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{
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query: z.string().describe("自然語言描述要找的工作流,如「把資料寫進 Google Sheets」"),
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},
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async ({ query }) => {
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try {
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if (!env.CYPHER_EXECUTOR) {
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return {
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content: [{ type: "text", text: "Error: CYPHER_EXECUTOR service binding is not configured." }],
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isError: true,
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};
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}
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const response = await env.CYPHER_EXECUTOR.fetch(
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`http://cypher-executor/workflows/search?q=${encodeURIComponent(query)}`,
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{ method: "GET", headers: { "X-Arcrun-API-Key": partnerToken } },
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);
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if (!response.ok) {
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const errorText = await response.text();
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return {
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content: [{ type: "text", text: `Search failed: ${errorText}` }],
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isError: true,
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};
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}
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const result = await response.json() as {
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entries?: Array<{ page_name?: string; content?: string }>;
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count?: number;
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mode?: string;
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capability_hint?: string;
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};
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const entries = result.entries ?? [];
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const count = result.count ?? entries.length;
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if (count === 0) {
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const hint = result.capability_hint ? `\n\n(${result.capability_hint})` : "";
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return {
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content: [{
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type: "text",
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text: `找不到符合「${query}」的現成工作流。可以用 u6u_deploy_workflow 部署一個新的。${hint}`,
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}],
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};
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}
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// capability_hint 透傳給 AI:未開語義時 AI 看到就能主動問用戶要不要開 Vectorize(R2.3 閉環)。
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const hintLine = result.capability_hint
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? `\n\n⚠️ ${result.capability_hint}`
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: "";
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return {
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content: [{
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type: "text",
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text: `找到 ${count} 個工作流(mode: ${result.mode ?? "keyword"}):\n${JSON.stringify(entries, null, 2)}${hintLine}`,
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}],
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};
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} catch (error) {
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return {
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content: [{ type: "text", text: `Internal Error: ${error instanceof Error ? error.message : String(error)}` }],
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isError: true,
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};
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}
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}
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);
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}
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