qmd/dist/mcp/server.js

/**
 * QMD MCP Server - Model Context Protocol server for QMD
 *
 * Exposes QMD search and document retrieval as MCP tools and resources.
 * Documents are accessible via qmd:// URIs.
 *
 * Follows MCP spec 2025-06-18 for proper response types.
 */
import { createServer } from "node:http";
import { randomUUID } from "node:crypto";
import { readFileSync } from "node:fs";
import { join, dirname } from "node:path";
import { fileURLToPath } from "url";
import { McpServer, ResourceTemplate } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { WebStandardStreamableHTTPServerTransport } from "@modelcontextprotocol/sdk/server/webStandardStreamableHttp.js";
import { isInitializeRequest } from "@modelcontextprotocol/sdk/types.js";
import { z } from "zod";
import { existsSync } from "fs";
import { createStore, extractSnippet, addLineNumbers, getDefaultDbPath, DEFAULT_MULTI_GET_MAX_BYTES, createEmbeddingProvider, resolveProviderKind, } from "../index.js";
import { getConfigPath } from "../collections.js";
/**
 * Build a query-side embedding provider (i-loazq6ze) for MCP server start.
 * Mirrors `buildQueryEmbedProvider` in the CLI: returns `undefined` when
 * the user has not opted into a remote provider, preserving pre-patch
 * behavior (local llama-cpp). Construction errors are logged and the
 * server falls back to the legacy path.
 */
function buildMcpEmbedProvider() {
    const env = process.env;
    const envOptIn = !!(env.QMD_EMBED_PROVIDER ||
        env.QMD_EMBED_ENDPOINT ||
        env.QMD_EMBED_AUTO_FALLBACK);
    // Probe resolved kind via the factory's standard precedence (env + config).
    const resolved = resolveProviderKind({});
    if (!envOptIn && resolved === "local")
        return undefined;
    try {
        return createEmbeddingProvider({});
    }
    catch (err) {
        // Log + fall through to undefined so legacy local path is used.
        process.stderr.write(`[qmd mcp] WARN failed to build embedding provider — using local fallback: ${err instanceof Error ? err.message : String(err)}\n`);
        return undefined;
    }
}
// =============================================================================
// Helper functions
// =============================================================================
/**
 * Encode a path for use in qmd:// URIs.
 * Encodes special characters but preserves forward slashes for readability.
 */
function encodeQmdPath(path) {
    // Encode each path segment separately to preserve slashes
    return path.split('/').map(segment => encodeURIComponent(segment)).join('/');
}
/**
 * Format search results as human-readable text summary
 */
function formatSearchSummary(results, query) {
    if (results.length === 0) {
        return `No results found for "${query}"`;
    }
    const lines = [`Found ${results.length} result${results.length === 1 ? '' : 's'} for "${query}":\n`];
    for (const r of results) {
        lines.push(`${r.docid} ${Math.round(r.score * 100)}% ${r.file} - ${r.title}`);
    }
    return lines.join('\n');
}
function getPackageVersion() {
    try {
        const pkgPath = join(dirname(fileURLToPath(import.meta.url)), "../../package.json");
        const pkg = JSON.parse(readFileSync(pkgPath, "utf-8"));
        return pkg.version ?? "unknown";
    }
    catch {
        return "unknown";
    }
}
// =============================================================================
// MCP Server
// =============================================================================
/**
 * Build dynamic server instructions from actual index state.
 * Injected into the LLM's system prompt via MCP initialize response —
 * gives the LLM immediate context about what's searchable without a tool call.
 */
async function buildInstructions(store) {
    const status = await store.getStatus();
    const contexts = await store.listContexts();
    const globalCtx = await store.getGlobalContext();
    const lines = [];
    // --- What is this? ---
    lines.push(`QMD is your local search engine over ${status.totalDocuments} markdown documents.`);
    if (globalCtx)
        lines.push(`Context: ${globalCtx}`);
    // --- What's searchable? ---
    if (status.collections.length > 0) {
        lines.push("");
        lines.push("Collections (scope with `collection` parameter):");
        for (const col of status.collections) {
            // Find root context for this collection
            const rootCtx = contexts.find(c => c.collection === col.name && (c.path === "" || c.path === "/"));
            const desc = rootCtx ? ` — ${rootCtx.context}` : "";
            lines.push(`  - "${col.name}" (${col.documents} docs)${desc}`);
        }
    }
    // --- Capability gaps ---
    if (!status.hasVectorIndex) {
        lines.push("");
        lines.push("Note: No vector embeddings yet. Run `qmd embed` to enable semantic search (vec/hyde).");
    }
    else if (status.needsEmbedding > 0) {
        lines.push("");
        lines.push(`Note: ${status.needsEmbedding} documents need embedding. Run \`qmd embed\` to update.`);
    }
    // --- Search tool ---
    lines.push("");
    lines.push("Search: Use `query` with sub-queries (lex/vec/hyde):");
    lines.push("  - type:'lex' — BM25 keyword search (exact terms, fast)");
    lines.push("  - type:'vec' — semantic vector search (meaning-based)");
    lines.push("  - type:'hyde' — hypothetical document (write what the answer looks like)");
    lines.push("");
    lines.push("  Always provide `intent` on every search call to disambiguate and improve snippets.");
    lines.push("");
    lines.push("Examples:");
    lines.push("  Quick keyword lookup: [{type:'lex', query:'error handling'}]");
    lines.push("  Semantic search: [{type:'vec', query:'how to handle errors gracefully'}]");
    lines.push("  Best results: [{type:'lex', query:'error'}, {type:'vec', query:'error handling best practices'}]");
    lines.push("  With intent: searches=[{type:'lex', query:'performance'}], intent='web page load times'");
    // --- Retrieval workflow ---
    lines.push("");
    lines.push("Retrieval:");
    lines.push("  - `get` — single document by path or docid (#abc123). Supports line offset (`file.md:100`).");
    lines.push("  - `multi_get` — batch retrieve by glob (`journals/2025-05*.md`) or comma-separated list.");
    // --- Non-obvious things that prevent mistakes ---
    lines.push("");
    lines.push("Tips:");
    lines.push("  - File paths in results are relative to their collection.");
    lines.push("  - Use `minScore: 0.5` to filter low-confidence results.");
    lines.push("  - Results include a `context` field describing the content type.");
    return lines.join("\n");
}
/**
 * Create an MCP server with all QMD tools, resources, and prompts registered.
 * Shared by both stdio and HTTP transports.
 */
async function createMcpServer(store) {
    const server = new McpServer({ name: "qmd", version: getPackageVersion() }, { instructions: await buildInstructions(store) });
    // Pre-fetch default collection names for search tools
    const defaultCollectionNames = await store.getDefaultCollectionNames();
    // ---------------------------------------------------------------------------
    // Resource: qmd://{path} - read-only access to documents by path
    // Note: No list() - documents are discovered via search tools
    // ---------------------------------------------------------------------------
    server.registerResource("document", new ResourceTemplate("qmd://{+path}", { list: undefined }), {
        title: "QMD Document",
        description: "A markdown document from your QMD knowledge base. Use search tools to discover documents.",
        mimeType: "text/markdown",
    }, async (uri, { path }) => {
        // Decode URL-encoded path (MCP clients send encoded URIs)
        const pathStr = Array.isArray(path) ? path.join('/') : (path || '');
        const decodedPath = decodeURIComponent(pathStr);
        // Use SDK to find document — findDocument handles collection/path resolution
        const result = await store.get(decodedPath, { includeBody: true });
        if ("error" in result) {
            return { contents: [{ uri: uri.href, text: `Document not found: ${decodedPath}` }] };
        }
        let text = addLineNumbers(result.body || ""); // Default to line numbers
        if (result.context) {
            text = `<!-- Context: ${result.context} -->\n\n` + text;
        }
        return {
            contents: [{
                    uri: uri.href,
                    name: result.displayPath,
                    title: result.title || result.displayPath,
                    mimeType: "text/markdown",
                    text,
                }],
        };
    });
    // ---------------------------------------------------------------------------
    // Tool: query (Primary search tool)
    // ---------------------------------------------------------------------------
    const subSearchSchema = z.object({
        type: z.enum(['lex', 'vec', 'hyde']).describe("lex = BM25 keywords (supports \"phrase\" and -negation); " +
            "vec = semantic question; hyde = hypothetical answer passage"),
        query: z.string().describe("The query text. For lex: use keywords, \"quoted phrases\", and -negation. " +
            "For vec: natural language question. For hyde: 50-100 word answer passage."),
    });
    server.registerTool("query", {
        title: "Query",
        description: `Search the knowledge base using a query document — one or more typed sub-queries combined for best recall.

## Query Types

**lex** — BM25 keyword search. Fast, exact, no LLM needed.
Full lex syntax:
- \`term\` — prefix match ("perf" matches "performance")
- \`"exact phrase"\` — phrase must appear verbatim
- \`-term\` or \`-"phrase"\` — exclude documents containing this

Good lex examples:
- \`"connection pool" timeout -redis\`
- \`"machine learning" -sports -athlete\`
- \`handleError async typescript\`

**vec** — Semantic vector search. Write a natural language question. Finds documents by meaning, not exact words.
- \`how does the rate limiter handle burst traffic?\`
- \`what is the tradeoff between consistency and availability?\`

**hyde** — Hypothetical document. Write 50-100 words that look like the answer. Often the most powerful for nuanced topics.
- \`The rate limiter uses a token bucket algorithm. When a client exceeds 100 req/min, subsequent requests return 429 until the window resets.\`

## Strategy

Combine types for best results. First sub-query gets 2× weight — put your strongest signal first.

| Goal | Approach |
|------|----------|
| Know exact term/name | \`lex\` only |
| Concept search | \`vec\` only |
| Best recall | \`lex\` + \`vec\` |
| Complex/nuanced | \`lex\` + \`vec\` + \`hyde\` |
| Unknown vocabulary | Use a standalone natural-language query (no typed lines) so the server can auto-expand it |

## Examples

Simple lookup:
\`\`\`json
[{ "type": "lex", "query": "CAP theorem" }]
\`\`\`

Best recall on a technical topic:
\`\`\`json
[
  { "type": "lex", "query": "\\"connection pool\\" timeout -redis" },
  { "type": "vec", "query": "why do database connections time out under load" },
  { "type": "hyde", "query": "Connection pool exhaustion occurs when all connections are in use and new requests must wait. This typically happens under high concurrency when queries run longer than expected." }
]
\`\`\`

Intent-aware lex (C++ performance, not sports):
\`\`\`json
[
  { "type": "lex", "query": "\\"C++ performance\\" optimization -sports -athlete" },
  { "type": "vec", "query": "how to optimize C++ program performance" }
]
\`\`\``,
        annotations: { readOnlyHint: true, openWorldHint: false },
        inputSchema: {
            searches: z.array(subSearchSchema).min(1).max(10).describe("Typed sub-queries to execute (lex/vec/hyde). First gets 2x weight."),
            limit: z.number().optional().default(10).describe("Max results (default: 10)"),
            minScore: z.number().optional().default(0).describe("Min relevance 0-1 (default: 0)"),
            candidateLimit: z.number().optional().describe("Maximum candidates to rerank (default: 40, lower = faster but may miss results)"),
            collections: z.array(z.string()).optional().describe("Filter to collections (OR match)"),
            intent: z.string().optional().describe("Background context to disambiguate the query. Example: query='performance', intent='web page load times and Core Web Vitals'. Does not search on its own."),
            rerank: z.boolean().optional().default(true).describe("Rerank results using LLM (default: true). Set to false for faster results on CPU-only machines."),
        },
    }, async ({ searches, limit, minScore, candidateLimit, collections, intent, rerank }) => {
        // Map to internal format
        const queries = searches.map(s => ({
            type: s.type,
            query: s.query,
        }));
        // Use default collections if none specified
        const effectiveCollections = collections ?? defaultCollectionNames;
        const results = await store.search({
            queries,
            collections: effectiveCollections.length > 0 ? effectiveCollections : undefined,
            limit,
            minScore,
            rerank,
            intent,
        });
        // Use first lex or vec query for snippet extraction
        const primaryQuery = searches.find(s => s.type === 'lex')?.query
            || searches.find(s => s.type === 'vec')?.query
            || searches[0]?.query || "";
        const filtered = results.map(r => {
            const { line, snippet } = extractSnippet(r.bestChunk, primaryQuery, 300, undefined, undefined, intent);
            return {
                docid: `#${r.docid}`,
                file: r.displayPath,
                title: r.title,
                score: Math.round(r.score * 100) / 100,
                context: r.context,
                snippet: addLineNumbers(snippet, line),
            };
        });
        return {
            content: [{ type: "text", text: formatSearchSummary(filtered, primaryQuery) }],
            structuredContent: { results: filtered },
        };
    });
    // ---------------------------------------------------------------------------
    // Tool: qmd_get (Retrieve document)
    // ---------------------------------------------------------------------------
    server.registerTool("get", {
        title: "Get Document",
        description: "Retrieve the full content of a document by its file path or docid. Use paths or docids (#abc123) from search results. Suggests similar files if not found.",
        annotations: { readOnlyHint: true, openWorldHint: false },
        inputSchema: {
            file: z.string().describe("File path or docid from search results (e.g., 'pages/meeting.md', '#abc123', or 'pages/meeting.md:100' to start at line 100)"),
            fromLine: z.number().optional().describe("Start from this line number (1-indexed)"),
            maxLines: z.number().optional().describe("Maximum number of lines to return"),
            lineNumbers: z.boolean().optional().default(false).describe("Add line numbers to output (format: 'N: content')"),
        },
    }, async ({ file, fromLine, maxLines, lineNumbers }) => {
        // Support :line suffix in `file` (e.g. "foo.md:120") when fromLine isn't provided
        let parsedFromLine = fromLine;
        let lookup = file;
        const colonMatch = lookup.match(/:(\d+)$/);
        if (colonMatch && colonMatch[1] && parsedFromLine === undefined) {
            parsedFromLine = parseInt(colonMatch[1], 10);
            lookup = lookup.slice(0, -colonMatch[0].length);
        }
        const result = await store.get(lookup, { includeBody: false });
        if ("error" in result) {
            let msg = `Document not found: ${file}`;
            if (result.similarFiles.length > 0) {
                msg += `\n\nDid you mean one of these?\n${result.similarFiles.map(s => `  - ${s}`).join('\n')}`;
            }
            return {
                content: [{ type: "text", text: msg }],
                isError: true,
            };
        }
        const body = await store.getDocumentBody(result.filepath, { fromLine: parsedFromLine, maxLines }) ?? "";
        let text = body;
        if (lineNumbers) {
            const startLine = parsedFromLine || 1;
            text = addLineNumbers(text, startLine);
        }
        if (result.context) {
            text = `<!-- Context: ${result.context} -->\n\n` + text;
        }
        return {
            content: [{
                    type: "resource",
                    resource: {
                        uri: `qmd://${encodeQmdPath(result.displayPath)}`,
                        name: result.displayPath,
                        title: result.title,
                        mimeType: "text/markdown",
                        text,
                    },
                }],
        };
    });
    // ---------------------------------------------------------------------------
    // Tool: qmd_multi_get (Retrieve multiple documents)
    // ---------------------------------------------------------------------------
    server.registerTool("multi_get", {
        title: "Multi-Get Documents",
        description: "Retrieve multiple documents by glob pattern (e.g., 'journals/2025-05*.md') or comma-separated list. Skips files larger than maxBytes.",
        annotations: { readOnlyHint: true, openWorldHint: false },
        inputSchema: {
            pattern: z.string().describe("Glob pattern or comma-separated list of file paths"),
            maxLines: z.number().optional().describe("Maximum lines per file"),
            maxBytes: z.number().optional().default(10240).describe("Skip files larger than this (default: 10240 = 10KB)"),
            lineNumbers: z.boolean().optional().default(false).describe("Add line numbers to output (format: 'N: content')"),
        },
    }, async ({ pattern, maxLines, maxBytes, lineNumbers }) => {
        const { docs, errors } = await store.multiGet(pattern, { includeBody: true, maxBytes: maxBytes || DEFAULT_MULTI_GET_MAX_BYTES });
        if (docs.length === 0 && errors.length === 0) {
            return {
                content: [{ type: "text", text: `No files matched pattern: ${pattern}` }],
                isError: true,
            };
        }
        const content = [];
        if (errors.length > 0) {
            content.push({ type: "text", text: `Errors:\n${errors.join('\n')}` });
        }
        for (const result of docs) {
            if (result.skipped) {
                content.push({
                    type: "text",
                    text: `[SKIPPED: ${result.doc.displayPath} - ${result.skipReason}. Use 'qmd_get' with file="${result.doc.displayPath}" to retrieve.]`,
                });
                continue;
            }
            let text = result.doc.body || "";
            if (maxLines !== undefined) {
                const lines = text.split("\n");
                text = lines.slice(0, maxLines).join("\n");
                if (lines.length > maxLines) {
                    text += `\n\n[... truncated ${lines.length - maxLines} more lines]`;
                }
            }
            if (lineNumbers) {
                text = addLineNumbers(text);
            }
            if (result.doc.context) {
                text = `<!-- Context: ${result.doc.context} -->\n\n` + text;
            }
            content.push({
                type: "resource",
                resource: {
                    uri: `qmd://${encodeQmdPath(result.doc.displayPath)}`,
                    name: result.doc.displayPath,
                    title: result.doc.title,
                    mimeType: "text/markdown",
                    text,
                },
            });
        }
        return { content };
    });
    // ---------------------------------------------------------------------------
    // Tool: qmd_status (Index status)
    // ---------------------------------------------------------------------------
    server.registerTool("status", {
        title: "Index Status",
        description: "Show the status of the QMD index: collections, document counts, and health information.",
        annotations: { readOnlyHint: true, openWorldHint: false },
        inputSchema: {},
    }, async () => {
        const status = await store.getStatus();
        const summary = [
            `QMD Index Status:`,
            `  Total documents: ${status.totalDocuments}`,
            `  Needs embedding: ${status.needsEmbedding}`,
            `  Vector index: ${status.hasVectorIndex ? 'yes' : 'no'}`,
            `  Collections: ${status.collections.length}`,
        ];
        for (const col of status.collections) {
            summary.push(`    - ${col.name}: ${col.path} (${col.documents} docs)`);
        }
        return {
            content: [{ type: "text", text: summary.join('\n') }],
            structuredContent: status,
        };
    });
    return server;
}
// =============================================================================
// Transport: stdio (default)
// =============================================================================
export async function startMcpServer() {
    const configPath = getConfigPath();
    const embedProvider = buildMcpEmbedProvider();
    const store = await createStore({
        dbPath: getDefaultDbPath(),
        ...(existsSync(configPath) ? { configPath } : {}),
        ...(embedProvider ? { embedProvider } : {}),
    });
    const server = await createMcpServer(store);
    const transport = new StdioServerTransport();
    await server.connect(transport);
}
/**
 * Start MCP server over Streamable HTTP (JSON responses, no SSE).
 * Binds to localhost only. Returns a handle for shutdown and port discovery.
 */
export async function startMcpHttpServer(port, options) {
    const configPath = getConfigPath();
    const embedProvider = buildMcpEmbedProvider();
    const store = await createStore({
        dbPath: getDefaultDbPath(),
        ...(existsSync(configPath) ? { configPath } : {}),
        ...(embedProvider ? { embedProvider } : {}),
    });
    // Pre-fetch default collection names for REST endpoint
    const defaultCollectionNames = await store.getDefaultCollectionNames();
    // Session map: each client gets its own McpServer + Transport pair (MCP spec requirement).
    // The store is shared — it's stateless SQLite, safe for concurrent access.
    const sessions = new Map();
    async function createSession() {
        const transport = new WebStandardStreamableHTTPServerTransport({
            sessionIdGenerator: () => randomUUID(),
            enableJsonResponse: true,
            onsessioninitialized: (sessionId) => {
                sessions.set(sessionId, transport);
                log(`${ts()} New session ${sessionId} (${sessions.size} active)`);
            },
        });
        const server = await createMcpServer(store);
        await server.connect(transport);
        transport.onclose = () => {
            if (transport.sessionId) {
                sessions.delete(transport.sessionId);
            }
        };
        return transport;
    }
    const startTime = Date.now();
    const quiet = options?.quiet ?? false;
    /** Format timestamp for request logging */
    function ts() {
        return new Date().toISOString().slice(11, 23); // HH:mm:ss.SSS
    }
    /** Extract a human-readable label from a JSON-RPC body */
    function describeRequest(body) {
        const method = body?.method ?? "unknown";
        if (method === "tools/call") {
            const tool = body.params?.name ?? "?";
            const args = body.params?.arguments;
            // Show query string if present, truncated
            if (args?.query) {
                const q = String(args.query).slice(0, 80);
                return `tools/call ${tool} "${q}"`;
            }
            if (args?.path)
                return `tools/call ${tool} ${args.path}`;
            if (args?.pattern)
                return `tools/call ${tool} ${args.pattern}`;
            return `tools/call ${tool}`;
        }
        return method;
    }
    function log(msg) {
        if (!quiet)
            console.error(msg);
    }
    // Helper to collect request body
    async function collectBody(req) {
        const chunks = [];
        for await (const chunk of req)
            chunks.push(chunk);
        return Buffer.concat(chunks).toString();
    }
    const httpServer = createServer(async (nodeReq, nodeRes) => {
        const reqStart = Date.now();
        const pathname = nodeReq.url || "/";
        try {
            if (pathname === "/health" && nodeReq.method === "GET") {
                const body = JSON.stringify({ status: "ok", uptime: Math.floor((Date.now() - startTime) / 1000) });
                nodeRes.writeHead(200, { "Content-Type": "application/json" });
                nodeRes.end(body);
                log(`${ts()} GET /health (${Date.now() - reqStart}ms)`);
                return;
            }
            // REST endpoint: POST /search — structured search without MCP protocol
            // REST endpoint: POST /query (alias: /search) — structured search without MCP protocol
            if ((pathname === "/query" || pathname === "/search") && nodeReq.method === "POST") {
                const rawBody = await collectBody(nodeReq);
                const params = JSON.parse(rawBody);
                // Validate required fields
                if (!params.searches || !Array.isArray(params.searches)) {
                    nodeRes.writeHead(400, { "Content-Type": "application/json" });
                    nodeRes.end(JSON.stringify({ error: "Missing required field: searches (array)" }));
                    return;
                }
                // Map to internal format
                const queries = params.searches.map((s) => ({
                    type: s.type,
                    query: String(s.query || ""),
                }));
                // Use default collections if none specified
                const effectiveCollections = params.collections ?? defaultCollectionNames;
                const results = await store.search({
                    queries,
                    collections: effectiveCollections.length > 0 ? effectiveCollections : undefined,
                    limit: params.limit ?? 10,
                    minScore: params.minScore ?? 0,
                    intent: params.intent,
                });
                // Use first lex or vec query for snippet extraction
                const primaryQuery = params.searches.find((s) => s.type === 'lex')?.query
                    || params.searches.find((s) => s.type === 'vec')?.query
                    || params.searches[0]?.query || "";
                const formatted = results.map(r => {
                    const { line, snippet } = extractSnippet(r.bestChunk, primaryQuery, 300);
                    return {
                        docid: `#${r.docid}`,
                        file: r.displayPath,
                        title: r.title,
                        score: Math.round(r.score * 100) / 100,
                        context: r.context,
                        snippet: addLineNumbers(snippet, line),
                    };
                });
                nodeRes.writeHead(200, { "Content-Type": "application/json" });
                nodeRes.end(JSON.stringify({ results: formatted }));
                log(`${ts()} POST /query ${params.searches.length} queries (${Date.now() - reqStart}ms)`);
                return;
            }
            if (pathname === "/mcp" && nodeReq.method === "POST") {
                const rawBody = await collectBody(nodeReq);
                const body = JSON.parse(rawBody);
                const label = describeRequest(body);
                const url = `http://localhost:${port}${pathname}`;
                const headers = {};
                for (const [k, v] of Object.entries(nodeReq.headers)) {
                    if (typeof v === "string")
                        headers[k] = v;
                }
                // Route to existing session or create new one on initialize
                const sessionId = headers["mcp-session-id"];
                let transport;
                if (sessionId) {
                    const existing = sessions.get(sessionId);
                    if (!existing) {
                        nodeRes.writeHead(404, { "Content-Type": "application/json" });
                        nodeRes.end(JSON.stringify({
                            jsonrpc: "2.0",
                            error: { code: -32001, message: "Session not found" },
                            id: body?.id ?? null,
                        }));
                        return;
                    }
                    transport = existing;
                }
                else if (isInitializeRequest(body)) {
                    transport = await createSession();
                }
                else {
                    nodeRes.writeHead(400, { "Content-Type": "application/json" });
                    nodeRes.end(JSON.stringify({
                        jsonrpc: "2.0",
                        error: { code: -32000, message: "Bad Request: Missing session ID" },
                        id: body?.id ?? null,
                    }));
                    return;
                }
                const request = new Request(url, { method: "POST", headers, body: rawBody });
                const response = await transport.handleRequest(request, { parsedBody: body });
                nodeRes.writeHead(response.status, Object.fromEntries(response.headers));
                nodeRes.end(Buffer.from(await response.arrayBuffer()));
                log(`${ts()} POST /mcp ${label} (${Date.now() - reqStart}ms)`);
                return;
            }
            if (pathname === "/mcp") {
                const headers = {};
                for (const [k, v] of Object.entries(nodeReq.headers)) {
                    if (typeof v === "string")
                        headers[k] = v;
                }
                // GET/DELETE must have a valid session
                const sessionId = headers["mcp-session-id"];
                if (!sessionId) {
                    nodeRes.writeHead(400, { "Content-Type": "application/json" });
                    nodeRes.end(JSON.stringify({
                        jsonrpc: "2.0",
                        error: { code: -32000, message: "Bad Request: Missing session ID" },
                        id: null,
                    }));
                    return;
                }
                const transport = sessions.get(sessionId);
                if (!transport) {
                    nodeRes.writeHead(404, { "Content-Type": "application/json" });
                    nodeRes.end(JSON.stringify({
                        jsonrpc: "2.0",
                        error: { code: -32001, message: "Session not found" },
                        id: null,
                    }));
                    return;
                }
                const url = `http://localhost:${port}${pathname}`;
                const rawBody = nodeReq.method !== "GET" && nodeReq.method !== "HEAD" ? await collectBody(nodeReq) : undefined;
                const request = new Request(url, { method: nodeReq.method || "GET", headers, ...(rawBody ? { body: rawBody } : {}) });
                const response = await transport.handleRequest(request);
                nodeRes.writeHead(response.status, Object.fromEntries(response.headers));
                nodeRes.end(Buffer.from(await response.arrayBuffer()));
                return;
            }
            nodeRes.writeHead(404);
            nodeRes.end("Not Found");
        }
        catch (err) {
            console.error("HTTP handler error:", err);
            nodeRes.writeHead(500);
            nodeRes.end("Internal Server Error");
        }
    });
    await new Promise((resolve, reject) => {
        httpServer.on("error", reject);
        httpServer.listen(port, "localhost", () => resolve());
    });
    const actualPort = httpServer.address().port;
    let stopping = false;
    const stop = async () => {
        if (stopping)
            return;
        stopping = true;
        for (const transport of sessions.values()) {
            await transport.close();
        }
        sessions.clear();
        httpServer.close();
        await store.close();
        // Dispose the query-side embedding provider (if any) — releases
        // HTTP keep-alive sockets in OpenAIEmbeddingsProvider (i-loazq6ze).
        if (embedProvider) {
            try {
                await embedProvider.dispose();
            }
            catch { /* ignore */ }
        }
    };
    process.on("SIGTERM", async () => {
        console.error("Shutting down (SIGTERM)...");
        await stop();
        process.exit(0);
    });
    process.on("SIGINT", async () => {
        console.error("Shutting down (SIGINT)...");
        await stop();
        process.exit(0);
    });
    log(`QMD MCP server listening on http://localhost:${actualPort}/mcp`);
    return { httpServer, port: actualPort, stop };
}
// Run if this is the main module
if (fileURLToPath(import.meta.url) === process.argv[1] || process.argv[1]?.endsWith("/server.ts") || process.argv[1]?.endsWith("/server.js")) {
    startMcpServer().catch(console.error);
}