- bun workspaces + Turborepo monorepo (apps/web, apps/mcp; packages/*, scripts) - @mcpedia/core single business-logic layer (Document/Content/Search services) - @mcpedia/db Drizzle schema: documents + weighted tsvector (GIN) for FTS - @mcpedia/parser frontmatter, @mcpedia/search Postgres FTS (ts_rank+ts_headline) - Next.js 16 Web UI (home/doc SSG, search dynamic) + react-markdown render - MCP server (stdio) with 4 tools + in-memory smoke test - scripts/indexer walks content/ -> upserts into Postgres - 4 seed docs; README + PHASES status
97 lines
2.8 KiB
TypeScript
97 lines
2.8 KiB
TypeScript
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
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import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
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import { z } from "zod";
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import { listDocuments, getDocument, getRelated } from "@mcpedia/core";
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import { keywordSearch } from "@mcpedia/search";
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export function createMcpServer(): McpServer {
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const server = new McpServer({
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name: "mcpedia",
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version: "0.1.0",
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});
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server.registerTool(
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"search_documents",
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{
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description:
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"Full-text search across the MCPedia knowledge base (Postgres FTS). Returns ranked documents with a headline snippet.",
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inputSchema: z.object({
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query: z.string().describe("Free-text search query"),
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limit: z.number().int().positive().max(50).optional(),
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}),
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},
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async ({ query, limit }) => {
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const hits = await keywordSearch(query, limit ?? 20);
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return {
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content: [{ type: "text", text: JSON.stringify(hits, null, 2) }],
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};
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},
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);
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server.registerTool(
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"get_document",
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{
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description:
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"Fetch the full markdown body of a document by its slug (e.g. 'docs/websocket/contract').",
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inputSchema: z.object({
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slug: z.string().describe("Document slug, e.g. 'docs/websocket/contract'"),
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}),
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},
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async ({ slug }) => {
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const doc = await getDocument(slug);
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if (!doc) {
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return {
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content: [{ type: "text", text: `Document not found: ${slug}` }],
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isError: true,
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};
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}
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return { content: [{ type: "text", text: doc.body }] };
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},
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);
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server.registerTool(
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"list_documents",
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{
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description: "List documents, optionally filtered by section.",
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inputSchema: z.object({
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section: z
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.enum(["docs", "writeups", "research", "notes"])
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.optional(),
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}),
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},
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async ({ section }) => {
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const docs = await listDocuments({ section });
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return {
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content: [{ type: "text", text: JSON.stringify(docs, null, 2) }],
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};
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},
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);
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server.registerTool(
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"get_related_documents",
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{
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description: "Return documents that share tags with the given slug.",
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inputSchema: z.object({
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slug: z.string(),
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limit: z.number().int().positive().max(20).optional(),
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}),
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},
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async ({ slug, limit }) => {
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const related = await getRelated(slug, limit ?? 5);
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return {
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content: [{ type: "text", text: JSON.stringify(related, null, 2) }],
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};
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},
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);
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return server;
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}
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// When run directly (bun run src/index.ts), serve over stdio.
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const isMain =
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process.argv[1] && import.meta.url === `file://${process.argv[1]}`;
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if (isMain) {
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const transport = new StdioServerTransport();
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await createMcpServer().connect(transport);
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}
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