c648d5d8d2
* feat: add knowledge agent types, store, builder, and renderer Phase 1 of Knowledge Agents feature. Introduces corpus compilation pipeline that filters observations from the database into portable corpus files stored at ~/.claude-mem/corpora/. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add corpus CRUD HTTP endpoints and wire into worker service Phase 2 of Knowledge Agents. Adds CorpusRoutes with 5 endpoints (build, list, get, delete, rebuild) and registers them during worker background initialization alongside SearchRoutes. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add KnowledgeAgent with V1 SDK prime/query/reprime Phase 3 of Knowledge Agents. Uses Agent SDK V1 query() with resume and disallowedTools for Q&A-only knowledge sessions. Auto-reprimes on session expiry. Adds prime, query, and reprime HTTP endpoints to CorpusRoutes. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add MCP tools and skill for knowledge agents Phase 4 of Knowledge Agents. Adds build_corpus, list_corpora, prime_corpus, and query_corpus MCP tools delegating to worker HTTP endpoints. Includes /knowledge-agent skill with workflow docs. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: handle SDK process exit in KnowledgeAgent, add e2e test The Agent SDK may throw after yielding all messages when the Claude process exits with a non-zero code. Now tolerates this if session_id/answer were already captured. Adds comprehensive e2e test script (31 assertions) orchestrated via tmux-cli. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: use settings model ID instead of hardcoded model in KnowledgeAgent Reads CLAUDE_MEM_MODEL from user settings via getModelId(), matching the existing SDKAgent pattern. No more hardcoded model assumptions. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: improve knowledge agents developer experience Add public documentation page, rebuild/reprime MCP tools, and actionable error messages. DX review scored knowledge agents 4/10 — core engineering works (31/31 e2e) but the feature was invisible. This addresses discoverability (docs, cross-links), API completeness (missing MCP tools), and error quality (fix/example fields in error responses). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: add quick start guide to knowledge agents page Covers the three main use cases upfront: creating an agent, asking a single question, and starting a fresh conversation with reprime. Includes keeping-it-current section for rebuild + reprime workflow. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: address code review issues — path traversal, session safety, prompt injection - Block path traversal in CorpusStore with alphanumeric name validation and resolved path check - Harden system prompt against instruction injection from untrusted corpus content - Validate question field as non-empty string in query endpoint - Only persist session_id after successful prime (not null on failure) - Persist refreshed session_id after query execution - Only auto-reprime on session resume errors, not all query failures - Add fenced code block language tags to SKILL.md Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: address remaining code review issues — e2e robustness, MCP validation, docs - Harden e2e curl wrappers with connect-timeout, fallback to HTTP 000 on transport failure - Use curl_post wrapper consistently for all long-running POST calls - Add runtime name validation to all corpus MCP tool handlers - Fix docs: soften hallucination guarantee to probabilistic claim - Fix architecture diagram: add missing rebuild_corpus and reprime_corpus tools Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: enforce string[] type in safeParseJsonArray for corpus data integrity Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: add blank line before fenced code blocks in SKILL.md maintenance section Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
686 lines
24 KiB
TypeScript
686 lines
24 KiB
TypeScript
/**
|
|
* Claude-mem MCP Search Server - Thin HTTP Wrapper
|
|
*
|
|
* Refactored from 2,718 lines to ~600-800 lines
|
|
* Delegates all business logic to Worker HTTP API at localhost:37777
|
|
* Maintains MCP protocol handling and tool schemas
|
|
*/
|
|
|
|
// Version injected at build time by esbuild define
|
|
declare const __DEFAULT_PACKAGE_VERSION__: string;
|
|
const packageVersion = typeof __DEFAULT_PACKAGE_VERSION__ !== 'undefined' ? __DEFAULT_PACKAGE_VERSION__ : '0.0.0-dev';
|
|
|
|
// Import logger first
|
|
import { logger } from '../utils/logger.js';
|
|
|
|
// CRITICAL: Redirect console to stderr BEFORE other imports
|
|
// MCP uses stdio transport where stdout is reserved for JSON-RPC protocol messages.
|
|
// Any logs to stdout break the protocol (Claude Desktop parses "[2025..." as JSON array).
|
|
console['log'] = (...args: any[]) => {
|
|
logger.error('CONSOLE', 'Intercepted console output (MCP protocol protection)', undefined, { args });
|
|
};
|
|
|
|
import { Server } from '@modelcontextprotocol/sdk/server/index.js';
|
|
import { StdioServerTransport } from '@modelcontextprotocol/sdk/server/stdio.js';
|
|
import {
|
|
CallToolRequestSchema,
|
|
ListToolsRequestSchema,
|
|
} from '@modelcontextprotocol/sdk/types.js';
|
|
import { getWorkerPort, workerHttpRequest } from '../shared/worker-utils.js';
|
|
import { ensureWorkerStarted } from '../services/worker-spawner.js';
|
|
import { searchCodebase, formatSearchResults } from '../services/smart-file-read/search.js';
|
|
import { parseFile, formatFoldedView, unfoldSymbol } from '../services/smart-file-read/parser.js';
|
|
import { readFile } from 'node:fs/promises';
|
|
import { existsSync } from 'node:fs';
|
|
import { dirname, resolve } from 'node:path';
|
|
import { fileURLToPath } from 'node:url';
|
|
|
|
// Resolve the path to worker-service.cjs, which lives alongside mcp-server.cjs
|
|
// in the plugin's scripts directory. We need an explicit path because the MCP
|
|
// server runs under Node while the worker must run under Bun, so we can't rely
|
|
// on `__filename` pointing to a self-spawnable script.
|
|
//
|
|
// In the deployed CJS bundle, `__dirname` is always defined — the import.meta
|
|
// fallback only exists to keep the source future-proof against an eventual
|
|
// ESM port. Both fallback branches should be functionally unreachable today.
|
|
let mcpServerDirResolutionFailed = false;
|
|
const mcpServerDir = (() => {
|
|
if (typeof __dirname !== 'undefined') return __dirname;
|
|
try {
|
|
return dirname(fileURLToPath(import.meta.url));
|
|
} catch {
|
|
// Last-ditch fallback: cwd is almost certainly wrong, but throwing here
|
|
// would crash the MCP server before it can serve a single request. Mark
|
|
// the failure so the existence check below can produce a single, loud,
|
|
// root-cause-attributing log line instead of a confusing "missing worker
|
|
// bundle" warning that hides the dirname resolution failure.
|
|
mcpServerDirResolutionFailed = true;
|
|
return process.cwd();
|
|
}
|
|
})();
|
|
const WORKER_SCRIPT_PATH = resolve(mcpServerDir, 'worker-service.cjs');
|
|
|
|
/**
|
|
* Surface a clear, actionable error if the worker bundle isn't where we
|
|
* expect. Without this check, a missing or partial install only fails later
|
|
* inside spawnDaemon as a generic "failed to spawn" message.
|
|
*
|
|
* If dirname resolution itself failed (extremely unlikely in CJS), attribute
|
|
* the missing-bundle warning to the root cause so the user doesn't waste time
|
|
* looking for an install bug that doesn't exist.
|
|
*
|
|
* Called lazily from `ensureWorkerConnection` (not at module load) so that
|
|
* tests or tools that import this module without booting the MCP server
|
|
* don't see noisy ERROR-level log lines for a worker they never intended
|
|
* to start. The check is cheap and idempotent, so calling it on every
|
|
* auto-start attempt is fine.
|
|
*/
|
|
function errorIfWorkerScriptMissing(): void {
|
|
// Only log here when the dirname resolution itself failed — that's the
|
|
// mcp-server-specific root cause attribution that the spawner cannot
|
|
// provide. The plain "missing bundle" case is already covered by the
|
|
// existsSync guard inside ensureWorkerStarted, and logging from both
|
|
// sites would produce a confusing double-log on the same code path.
|
|
if (!mcpServerDirResolutionFailed) return;
|
|
if (existsSync(WORKER_SCRIPT_PATH)) return;
|
|
|
|
logger.error(
|
|
'SYSTEM',
|
|
'mcp-server: dirname resolution failed (both __dirname and import.meta.url are unavailable). Fell back to process.cwd() and the resolved WORKER_SCRIPT_PATH does not exist. This is the actual problem — the worker bundle is fine, but mcp-server cannot locate it. Worker auto-start will fail until the dirname-resolution path is fixed.',
|
|
{ workerScriptPath: WORKER_SCRIPT_PATH, mcpServerDir }
|
|
);
|
|
}
|
|
|
|
/**
|
|
* Map tool names to Worker HTTP endpoints
|
|
*/
|
|
const TOOL_ENDPOINT_MAP: Record<string, string> = {
|
|
'search': '/api/search',
|
|
'timeline': '/api/timeline'
|
|
};
|
|
|
|
/**
|
|
* Call Worker HTTP API endpoint (uses socket or TCP automatically)
|
|
*/
|
|
async function callWorkerAPI(
|
|
endpoint: string,
|
|
params: Record<string, any>
|
|
): Promise<{ content: Array<{ type: 'text'; text: string }>; isError?: boolean }> {
|
|
logger.debug('SYSTEM', '→ Worker API', undefined, { endpoint, params });
|
|
|
|
try {
|
|
const searchParams = new URLSearchParams();
|
|
|
|
// Convert params to query string
|
|
for (const [key, value] of Object.entries(params)) {
|
|
if (value !== undefined && value !== null) {
|
|
searchParams.append(key, String(value));
|
|
}
|
|
}
|
|
|
|
const apiPath = `${endpoint}?${searchParams}`;
|
|
const response = await workerHttpRequest(apiPath);
|
|
|
|
if (!response.ok) {
|
|
const errorText = await response.text();
|
|
throw new Error(`Worker API error (${response.status}): ${errorText}`);
|
|
}
|
|
|
|
const data = await response.json() as { content: Array<{ type: 'text'; text: string }>; isError?: boolean };
|
|
|
|
logger.debug('SYSTEM', '← Worker API success', undefined, { endpoint });
|
|
|
|
// Worker returns { content: [...] } format directly
|
|
return data;
|
|
} catch (error) {
|
|
logger.error('SYSTEM', '← Worker API error', { endpoint }, error as Error);
|
|
return {
|
|
content: [{
|
|
type: 'text' as const,
|
|
text: `Error calling Worker API: ${error instanceof Error ? error.message : String(error)}`
|
|
}],
|
|
isError: true
|
|
};
|
|
}
|
|
}
|
|
|
|
/**
|
|
* Call Worker HTTP API with POST body
|
|
*/
|
|
async function callWorkerAPIPost(
|
|
endpoint: string,
|
|
body: Record<string, any>
|
|
): Promise<{ content: Array<{ type: 'text'; text: string }>; isError?: boolean }> {
|
|
logger.debug('HTTP', 'Worker API request (POST)', undefined, { endpoint });
|
|
|
|
try {
|
|
const response = await workerHttpRequest(endpoint, {
|
|
method: 'POST',
|
|
headers: { 'Content-Type': 'application/json' },
|
|
body: JSON.stringify(body)
|
|
});
|
|
|
|
if (!response.ok) {
|
|
const errorText = await response.text();
|
|
throw new Error(`Worker API error (${response.status}): ${errorText}`);
|
|
}
|
|
|
|
const data = await response.json();
|
|
|
|
logger.debug('HTTP', 'Worker API success (POST)', undefined, { endpoint });
|
|
|
|
// Wrap raw data in MCP format
|
|
return {
|
|
content: [{
|
|
type: 'text' as const,
|
|
text: JSON.stringify(data, null, 2)
|
|
}]
|
|
};
|
|
} catch (error) {
|
|
logger.error('HTTP', 'Worker API error (POST)', { endpoint }, error as Error);
|
|
return {
|
|
content: [{
|
|
type: 'text' as const,
|
|
text: `Error calling Worker API: ${error instanceof Error ? error.message : String(error)}`
|
|
}],
|
|
isError: true
|
|
};
|
|
}
|
|
}
|
|
|
|
/**
|
|
* Verify Worker is accessible
|
|
*/
|
|
async function verifyWorkerConnection(): Promise<boolean> {
|
|
try {
|
|
const response = await workerHttpRequest('/api/health');
|
|
return response.ok;
|
|
} catch (error) {
|
|
// Expected during worker startup or if worker is down
|
|
logger.debug('SYSTEM', 'Worker health check failed', {}, error as Error);
|
|
return false;
|
|
}
|
|
}
|
|
|
|
/**
|
|
* Ensure Worker is available for Codex and other MCP-only clients.
|
|
* Claude hooks already start the worker; this path makes Codex turnkey.
|
|
*/
|
|
async function ensureWorkerConnection(): Promise<boolean> {
|
|
if (await verifyWorkerConnection()) {
|
|
return true;
|
|
}
|
|
|
|
logger.warn('SYSTEM', 'Worker not available, attempting auto-start for MCP client');
|
|
|
|
// Validate the worker bundle path lazily here (rather than at module load)
|
|
// so that tests/tools that import this module without booting the MCP
|
|
// server don't see noisy ERROR-level log lines for a worker they never
|
|
// intended to start.
|
|
errorIfWorkerScriptMissing();
|
|
|
|
try {
|
|
const port = getWorkerPort();
|
|
const started = await ensureWorkerStarted(port, WORKER_SCRIPT_PATH);
|
|
if (!started) {
|
|
logger.error(
|
|
'SYSTEM',
|
|
'Worker auto-start returned false — MCP tools that require the worker (search, timeline, get_observations) will fail until the worker is running. Check earlier log lines for the specific failure reason (Bun not found, missing worker bundle, port conflict, etc.).'
|
|
);
|
|
}
|
|
return started;
|
|
} catch (error) {
|
|
logger.error(
|
|
'SYSTEM',
|
|
'Worker auto-start threw — MCP tools that require the worker (search, timeline, get_observations) will fail until the worker is running.',
|
|
undefined,
|
|
error as Error
|
|
);
|
|
return false;
|
|
}
|
|
}
|
|
|
|
/**
|
|
* Tool definitions with HTTP-based handlers
|
|
* Minimal descriptions - use help() tool with operation parameter for detailed docs
|
|
*/
|
|
const tools = [
|
|
{
|
|
name: '__IMPORTANT',
|
|
description: `3-LAYER WORKFLOW (ALWAYS FOLLOW):
|
|
1. search(query) → Get index with IDs (~50-100 tokens/result)
|
|
2. timeline(anchor=ID) → Get context around interesting results
|
|
3. get_observations([IDs]) → Fetch full details ONLY for filtered IDs
|
|
NEVER fetch full details without filtering first. 10x token savings.`,
|
|
inputSchema: {
|
|
type: 'object',
|
|
properties: {}
|
|
},
|
|
handler: async () => ({
|
|
content: [{
|
|
type: 'text' as const,
|
|
text: `# Memory Search Workflow
|
|
|
|
**3-Layer Pattern (ALWAYS follow this):**
|
|
|
|
1. **Search** - Get index of results with IDs
|
|
\`search(query="...", limit=20, project="...")\`
|
|
Returns: Table with IDs, titles, dates (~50-100 tokens/result)
|
|
|
|
2. **Timeline** - Get context around interesting results
|
|
\`timeline(anchor=<ID>, depth_before=3, depth_after=3)\`
|
|
Returns: Chronological context showing what was happening
|
|
|
|
3. **Fetch** - Get full details ONLY for relevant IDs
|
|
\`get_observations(ids=[...])\` # ALWAYS batch for 2+ items
|
|
Returns: Complete details (~500-1000 tokens/result)
|
|
|
|
**Why:** 10x token savings. Never fetch full details without filtering first.`
|
|
}]
|
|
})
|
|
},
|
|
{
|
|
name: 'search',
|
|
description: 'Step 1: Search memory. Returns index with IDs. Params: query, limit, project, type, obs_type, dateStart, dateEnd, offset, orderBy',
|
|
inputSchema: {
|
|
type: 'object',
|
|
properties: {},
|
|
additionalProperties: true
|
|
},
|
|
handler: async (args: any) => {
|
|
const endpoint = TOOL_ENDPOINT_MAP['search'];
|
|
return await callWorkerAPI(endpoint, args);
|
|
}
|
|
},
|
|
{
|
|
name: 'timeline',
|
|
description: 'Step 2: Get context around results. Params: anchor (observation ID) OR query (finds anchor automatically), depth_before, depth_after, project',
|
|
inputSchema: {
|
|
type: 'object',
|
|
properties: {},
|
|
additionalProperties: true
|
|
},
|
|
handler: async (args: any) => {
|
|
const endpoint = TOOL_ENDPOINT_MAP['timeline'];
|
|
return await callWorkerAPI(endpoint, args);
|
|
}
|
|
},
|
|
{
|
|
name: 'get_observations',
|
|
description: 'Step 3: Fetch full details for filtered IDs. Params: ids (array of observation IDs, required), orderBy, limit, project',
|
|
inputSchema: {
|
|
type: 'object',
|
|
properties: {
|
|
ids: {
|
|
type: 'array',
|
|
items: { type: 'number' },
|
|
description: 'Array of observation IDs to fetch (required)'
|
|
}
|
|
},
|
|
required: ['ids'],
|
|
additionalProperties: true
|
|
},
|
|
handler: async (args: any) => {
|
|
return await callWorkerAPIPost('/api/observations/batch', args);
|
|
}
|
|
},
|
|
{
|
|
name: 'smart_search',
|
|
description: 'Search codebase for symbols, functions, classes using tree-sitter AST parsing. Returns folded structural views with token counts. Use path parameter to scope the search.',
|
|
inputSchema: {
|
|
type: 'object',
|
|
properties: {
|
|
query: {
|
|
type: 'string',
|
|
description: 'Search term — matches against symbol names, file names, and file content'
|
|
},
|
|
path: {
|
|
type: 'string',
|
|
description: 'Root directory to search (default: current working directory)'
|
|
},
|
|
max_results: {
|
|
type: 'number',
|
|
description: 'Maximum results to return (default: 20)'
|
|
},
|
|
file_pattern: {
|
|
type: 'string',
|
|
description: 'Substring filter for file paths (e.g. ".ts", "src/services")'
|
|
}
|
|
},
|
|
required: ['query']
|
|
},
|
|
handler: async (args: any) => {
|
|
const rootDir = resolve(args.path || process.cwd());
|
|
const result = await searchCodebase(rootDir, args.query, {
|
|
maxResults: args.max_results || 20,
|
|
filePattern: args.file_pattern
|
|
});
|
|
const formatted = formatSearchResults(result, args.query);
|
|
return {
|
|
content: [{ type: 'text' as const, text: formatted }]
|
|
};
|
|
}
|
|
},
|
|
{
|
|
name: 'smart_unfold',
|
|
description: 'Expand a specific symbol (function, class, method) from a file. Returns the full source code of just that symbol. Use after smart_search or smart_outline to read specific code.',
|
|
inputSchema: {
|
|
type: 'object',
|
|
properties: {
|
|
file_path: {
|
|
type: 'string',
|
|
description: 'Path to the source file'
|
|
},
|
|
symbol_name: {
|
|
type: 'string',
|
|
description: 'Name of the symbol to unfold (function, class, method, etc.)'
|
|
}
|
|
},
|
|
required: ['file_path', 'symbol_name']
|
|
},
|
|
handler: async (args: any) => {
|
|
const filePath = resolve(args.file_path);
|
|
const content = await readFile(filePath, 'utf-8');
|
|
const unfolded = unfoldSymbol(content, filePath, args.symbol_name);
|
|
if (unfolded) {
|
|
return {
|
|
content: [{ type: 'text' as const, text: unfolded }]
|
|
};
|
|
}
|
|
// Symbol not found — show available symbols
|
|
const parsed = parseFile(content, filePath);
|
|
if (parsed.symbols.length > 0) {
|
|
const available = parsed.symbols.map(s => ` - ${s.name} (${s.kind})`).join('\n');
|
|
return {
|
|
content: [{
|
|
type: 'text' as const,
|
|
text: `Symbol "${args.symbol_name}" not found in ${args.file_path}.\n\nAvailable symbols:\n${available}`
|
|
}]
|
|
};
|
|
}
|
|
return {
|
|
content: [{
|
|
type: 'text' as const,
|
|
text: `Could not parse ${args.file_path}. File may be unsupported or empty.`
|
|
}]
|
|
};
|
|
}
|
|
},
|
|
{
|
|
name: 'smart_outline',
|
|
description: 'Get structural outline of a file — shows all symbols (functions, classes, methods, types) with signatures but bodies folded. Much cheaper than reading the full file.',
|
|
inputSchema: {
|
|
type: 'object',
|
|
properties: {
|
|
file_path: {
|
|
type: 'string',
|
|
description: 'Path to the source file'
|
|
}
|
|
},
|
|
required: ['file_path']
|
|
},
|
|
handler: async (args: any) => {
|
|
const filePath = resolve(args.file_path);
|
|
const content = await readFile(filePath, 'utf-8');
|
|
const parsed = parseFile(content, filePath);
|
|
if (parsed.symbols.length > 0) {
|
|
return {
|
|
content: [{ type: 'text' as const, text: formatFoldedView(parsed) }]
|
|
};
|
|
}
|
|
return {
|
|
content: [{
|
|
type: 'text' as const,
|
|
text: `Could not parse ${args.file_path}. File may use an unsupported language or be empty.`
|
|
}]
|
|
};
|
|
}
|
|
},
|
|
{
|
|
name: 'build_corpus',
|
|
description: 'Build a knowledge corpus from filtered observations. Creates a queryable knowledge agent. Params: name (required), description, project, types (comma-separated), concepts (comma-separated), files (comma-separated), query, dateStart, dateEnd, limit',
|
|
inputSchema: {
|
|
type: 'object',
|
|
properties: {
|
|
name: { type: 'string', description: 'Corpus name (used as filename)' },
|
|
description: { type: 'string', description: 'What this corpus is about' },
|
|
project: { type: 'string', description: 'Filter by project' },
|
|
types: { type: 'string', description: 'Comma-separated observation types: decision,bugfix,feature,refactor,discovery,change' },
|
|
concepts: { type: 'string', description: 'Comma-separated concepts to filter by' },
|
|
files: { type: 'string', description: 'Comma-separated file paths to filter by' },
|
|
query: { type: 'string', description: 'Semantic search query' },
|
|
dateStart: { type: 'string', description: 'Start date (ISO format)' },
|
|
dateEnd: { type: 'string', description: 'End date (ISO format)' },
|
|
limit: { type: 'number', description: 'Maximum observations (default 500)' }
|
|
},
|
|
required: ['name'],
|
|
additionalProperties: true
|
|
},
|
|
handler: async (args: any) => {
|
|
return await callWorkerAPIPost('/api/corpus', args);
|
|
}
|
|
},
|
|
{
|
|
name: 'list_corpora',
|
|
description: 'List all knowledge corpora with their stats and priming status',
|
|
inputSchema: {
|
|
type: 'object',
|
|
properties: {},
|
|
additionalProperties: true
|
|
},
|
|
handler: async (args: any) => {
|
|
return await callWorkerAPI('/api/corpus', args);
|
|
}
|
|
},
|
|
{
|
|
name: 'prime_corpus',
|
|
description: 'Prime a knowledge corpus — creates an AI session loaded with the corpus knowledge. Must be called before query_corpus.',
|
|
inputSchema: {
|
|
type: 'object',
|
|
properties: {
|
|
name: { type: 'string', description: 'Name of the corpus to prime' }
|
|
},
|
|
required: ['name'],
|
|
additionalProperties: true
|
|
},
|
|
handler: async (args: any) => {
|
|
const { name, ...rest } = args;
|
|
if (typeof name !== 'string' || name.trim() === '') throw new Error('Missing required argument: name');
|
|
return await callWorkerAPIPost(`/api/corpus/${encodeURIComponent(name)}/prime`, rest);
|
|
}
|
|
},
|
|
{
|
|
name: 'query_corpus',
|
|
description: 'Ask a question to a primed knowledge corpus. The corpus must be primed first with prime_corpus.',
|
|
inputSchema: {
|
|
type: 'object',
|
|
properties: {
|
|
name: { type: 'string', description: 'Name of the corpus to query' },
|
|
question: { type: 'string', description: 'The question to ask' }
|
|
},
|
|
required: ['name', 'question'],
|
|
additionalProperties: true
|
|
},
|
|
handler: async (args: any) => {
|
|
const { name, ...rest } = args;
|
|
if (typeof name !== 'string' || name.trim() === '') throw new Error('Missing required argument: name');
|
|
return await callWorkerAPIPost(`/api/corpus/${encodeURIComponent(name)}/query`, rest);
|
|
}
|
|
},
|
|
{
|
|
name: 'rebuild_corpus',
|
|
description: 'Rebuild a knowledge corpus from its stored filter — re-runs the search to refresh with new observations. Does not re-prime the session.',
|
|
inputSchema: {
|
|
type: 'object',
|
|
properties: {
|
|
name: { type: 'string', description: 'Name of the corpus to rebuild' }
|
|
},
|
|
required: ['name'],
|
|
additionalProperties: true
|
|
},
|
|
handler: async (args: any) => {
|
|
const { name, ...rest } = args;
|
|
if (typeof name !== 'string' || name.trim() === '') throw new Error('Missing required argument: name');
|
|
return await callWorkerAPIPost(`/api/corpus/${encodeURIComponent(name)}/rebuild`, rest);
|
|
}
|
|
},
|
|
{
|
|
name: 'reprime_corpus',
|
|
description: 'Create a fresh knowledge agent session for a corpus, clearing prior Q&A context. Use when conversation has drifted or after rebuilding.',
|
|
inputSchema: {
|
|
type: 'object',
|
|
properties: {
|
|
name: { type: 'string', description: 'Name of the corpus to reprime' }
|
|
},
|
|
required: ['name'],
|
|
additionalProperties: true
|
|
},
|
|
handler: async (args: any) => {
|
|
const { name, ...rest } = args;
|
|
if (typeof name !== 'string' || name.trim() === '') throw new Error('Missing required argument: name');
|
|
return await callWorkerAPIPost(`/api/corpus/${encodeURIComponent(name)}/reprime`, rest);
|
|
}
|
|
}
|
|
];
|
|
|
|
// Create the MCP server
|
|
const server = new Server(
|
|
{
|
|
name: 'claude-mem',
|
|
version: packageVersion,
|
|
},
|
|
{
|
|
capabilities: {
|
|
tools: {}, // Exposes tools capability (handled by ListToolsRequestSchema and CallToolRequestSchema)
|
|
},
|
|
}
|
|
);
|
|
|
|
// Register tools/list handler
|
|
server.setRequestHandler(ListToolsRequestSchema, async () => {
|
|
return {
|
|
tools: tools.map(tool => ({
|
|
name: tool.name,
|
|
description: tool.description,
|
|
inputSchema: tool.inputSchema
|
|
}))
|
|
};
|
|
});
|
|
|
|
// Register tools/call handler
|
|
server.setRequestHandler(CallToolRequestSchema, async (request) => {
|
|
const tool = tools.find(t => t.name === request.params.name);
|
|
|
|
if (!tool) {
|
|
throw new Error(`Unknown tool: ${request.params.name}`);
|
|
}
|
|
|
|
try {
|
|
return await tool.handler(request.params.arguments || {});
|
|
} catch (error) {
|
|
logger.error('SYSTEM', 'Tool execution failed', { tool: request.params.name }, error as Error);
|
|
return {
|
|
content: [{
|
|
type: 'text' as const,
|
|
text: `Tool execution failed: ${error instanceof Error ? error.message : String(error)}`
|
|
}],
|
|
isError: true
|
|
};
|
|
}
|
|
});
|
|
|
|
// Parent heartbeat: self-exit when parent dies (ppid=1 on Unix means orphaned)
|
|
// Prevents orphaned MCP server processes when Claude Code exits unexpectedly
|
|
const HEARTBEAT_INTERVAL_MS = 30_000;
|
|
let heartbeatTimer: ReturnType<typeof setInterval> | null = null;
|
|
let isCleaningUp = false;
|
|
|
|
function handleStdioClosed() {
|
|
cleanup('stdio-closed');
|
|
}
|
|
|
|
function handleStdioError(error: Error) {
|
|
logger.warn('SYSTEM', 'MCP stdio stream errored, shutting down', {
|
|
message: error.message
|
|
});
|
|
cleanup('stdio-error');
|
|
}
|
|
|
|
function attachStdioLifecycle() {
|
|
process.stdin.on('end', handleStdioClosed);
|
|
process.stdin.on('close', handleStdioClosed);
|
|
process.stdin.on('error', handleStdioError);
|
|
}
|
|
|
|
function detachStdioLifecycle() {
|
|
process.stdin.off('end', handleStdioClosed);
|
|
process.stdin.off('close', handleStdioClosed);
|
|
process.stdin.off('error', handleStdioError);
|
|
}
|
|
|
|
function startParentHeartbeat() {
|
|
// ppid-based orphan detection only works on Unix
|
|
if (process.platform === 'win32') return;
|
|
|
|
const initialPpid = process.ppid;
|
|
heartbeatTimer = setInterval(() => {
|
|
if (process.ppid === 1 || process.ppid !== initialPpid) {
|
|
logger.info('SYSTEM', 'Parent process died, self-exiting to prevent orphan', {
|
|
initialPpid,
|
|
currentPpid: process.ppid
|
|
});
|
|
cleanup();
|
|
}
|
|
}, HEARTBEAT_INTERVAL_MS);
|
|
|
|
// Don't let the heartbeat timer keep the process alive
|
|
if (heartbeatTimer.unref) heartbeatTimer.unref();
|
|
}
|
|
|
|
// Cleanup function — synchronous to ensure consistent behavior whether called
|
|
// from signal handlers, heartbeat interval, or awaited in async context
|
|
function cleanup(reason: string = 'shutdown') {
|
|
if (isCleaningUp) return;
|
|
isCleaningUp = true;
|
|
|
|
if (heartbeatTimer) clearInterval(heartbeatTimer);
|
|
detachStdioLifecycle();
|
|
logger.info('SYSTEM', 'MCP server shutting down', { reason });
|
|
process.exit(0);
|
|
}
|
|
|
|
// Register cleanup handlers for graceful shutdown
|
|
process.on('SIGTERM', cleanup);
|
|
process.on('SIGINT', cleanup);
|
|
|
|
// Start the server
|
|
async function main() {
|
|
// Start the MCP server
|
|
const transport = new StdioServerTransport();
|
|
attachStdioLifecycle();
|
|
await server.connect(transport);
|
|
logger.info('SYSTEM', 'Claude-mem search server started');
|
|
|
|
// Start parent heartbeat to detect orphaned MCP servers
|
|
startParentHeartbeat();
|
|
|
|
// Check Worker availability in background
|
|
setTimeout(async () => {
|
|
const workerAvailable = await ensureWorkerConnection();
|
|
if (!workerAvailable) {
|
|
logger.error('SYSTEM', 'Worker not available', undefined, {});
|
|
logger.error('SYSTEM', 'Tools will fail until Worker is started');
|
|
logger.error('SYSTEM', 'Start Worker with: npm run worker:restart');
|
|
} else {
|
|
logger.info('SYSTEM', 'Worker available', undefined, {});
|
|
}
|
|
}, 0);
|
|
}
|
|
|
|
main().catch((error) => {
|
|
logger.error('SYSTEM', 'Fatal error', undefined, error);
|
|
// Exit gracefully: Windows Terminal won't keep tab open on exit 0
|
|
// The wrapper/plugin will handle restart logic if needed
|
|
process.exit(0);
|
|
});
|