98920bd860
Adds save_memory MCP tool allowing users to manually save observations for semantic search. Source changes cherry-picked from PR #662 by @darconada (build artifact conflicts resolved by direct application). Closes #645. Co-Authored-By: darconadalabarga <darconada@arsys.es> Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
346 lines
10 KiB
TypeScript
346 lines
10 KiB
TypeScript
/**
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* Claude-mem MCP Search Server - Thin HTTP Wrapper
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*
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* Refactored from 2,718 lines to ~600-800 lines
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* Delegates all business logic to Worker HTTP API at localhost:37777
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* Maintains MCP protocol handling and tool schemas
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*/
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// Version injected at build time by esbuild define
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declare const __DEFAULT_PACKAGE_VERSION__: string;
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const packageVersion = typeof __DEFAULT_PACKAGE_VERSION__ !== 'undefined' ? __DEFAULT_PACKAGE_VERSION__ : '0.0.0-dev';
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// Import logger first
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import { logger } from '../utils/logger.js';
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// CRITICAL: Redirect console to stderr BEFORE other imports
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// MCP uses stdio transport where stdout is reserved for JSON-RPC protocol messages.
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// Any logs to stdout break the protocol (Claude Desktop parses "[2025..." as JSON array).
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const _originalLog = console['log'];
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console['log'] = (...args: any[]) => {
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logger.error('CONSOLE', 'Intercepted console output (MCP protocol protection)', undefined, { args });
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};
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import { Server } from '@modelcontextprotocol/sdk/server/index.js';
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import { StdioServerTransport } from '@modelcontextprotocol/sdk/server/stdio.js';
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import {
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CallToolRequestSchema,
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ListToolsRequestSchema,
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} from '@modelcontextprotocol/sdk/types.js';
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import { getWorkerPort, getWorkerHost } from '../shared/worker-utils.js';
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/**
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* Worker HTTP API configuration
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*/
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const WORKER_PORT = getWorkerPort();
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const WORKER_HOST = getWorkerHost();
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const WORKER_BASE_URL = `http://${WORKER_HOST}:${WORKER_PORT}`;
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/**
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* Map tool names to Worker HTTP endpoints
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*/
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const TOOL_ENDPOINT_MAP: Record<string, string> = {
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'search': '/api/search',
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'timeline': '/api/timeline'
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};
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/**
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* Call Worker HTTP API endpoint
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*/
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async function callWorkerAPI(
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endpoint: string,
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params: Record<string, any>
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): Promise<{ content: Array<{ type: 'text'; text: string }>; isError?: boolean }> {
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logger.debug('SYSTEM', '→ Worker API', undefined, { endpoint, params });
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try {
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const searchParams = new URLSearchParams();
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// Convert params to query string
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for (const [key, value] of Object.entries(params)) {
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if (value !== undefined && value !== null) {
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searchParams.append(key, String(value));
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}
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}
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const url = `${WORKER_BASE_URL}${endpoint}?${searchParams}`;
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const response = await fetch(url);
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if (!response.ok) {
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const errorText = await response.text();
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throw new Error(`Worker API error (${response.status}): ${errorText}`);
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}
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const data = await response.json() as { content: Array<{ type: 'text'; text: string }>; isError?: boolean };
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logger.debug('SYSTEM', '← Worker API success', undefined, { endpoint });
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// Worker returns { content: [...] } format directly
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return data;
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} catch (error) {
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logger.error('SYSTEM', '← Worker API error', { endpoint }, error as Error);
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return {
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content: [{
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type: 'text' as const,
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text: `Error calling Worker API: ${error instanceof Error ? error.message : String(error)}`
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}],
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isError: true
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};
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}
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}
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/**
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* Call Worker HTTP API with POST body
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*/
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async function callWorkerAPIPost(
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endpoint: string,
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body: Record<string, any>
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): Promise<{ content: Array<{ type: 'text'; text: string }>; isError?: boolean }> {
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logger.debug('HTTP', 'Worker API request (POST)', undefined, { endpoint });
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try {
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const url = `${WORKER_BASE_URL}${endpoint}`;
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const response = await fetch(url, {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json'
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},
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body: JSON.stringify(body)
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});
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if (!response.ok) {
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const errorText = await response.text();
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throw new Error(`Worker API error (${response.status}): ${errorText}`);
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}
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const data = await response.json();
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logger.debug('HTTP', 'Worker API success (POST)', undefined, { endpoint });
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// Wrap raw data in MCP format
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return {
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content: [{
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type: 'text' as const,
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text: JSON.stringify(data, null, 2)
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}]
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};
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} catch (error) {
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logger.error('HTTP', 'Worker API error (POST)', { endpoint }, error as Error);
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return {
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content: [{
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type: 'text' as const,
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text: `Error calling Worker API: ${error instanceof Error ? error.message : String(error)}`
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}],
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isError: true
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};
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}
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}
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/**
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* Verify Worker is accessible
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*/
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async function verifyWorkerConnection(): Promise<boolean> {
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try {
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const response = await fetch(`${WORKER_BASE_URL}/api/health`);
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return response.ok;
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} catch (error) {
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// Expected during worker startup or if worker is down
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logger.debug('SYSTEM', 'Worker health check failed', {}, error as Error);
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return false;
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}
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}
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/**
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* Tool definitions with HTTP-based handlers
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* Minimal descriptions - use help() tool with operation parameter for detailed docs
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*/
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const tools = [
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{
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name: '__IMPORTANT',
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description: `3-LAYER WORKFLOW (ALWAYS FOLLOW):
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1. search(query) → Get index with IDs (~50-100 tokens/result)
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2. timeline(anchor=ID) → Get context around interesting results
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3. get_observations([IDs]) → Fetch full details ONLY for filtered IDs
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NEVER fetch full details without filtering first. 10x token savings.`,
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inputSchema: {
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type: 'object',
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properties: {}
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},
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handler: async () => ({
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content: [{
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type: 'text' as const,
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text: `# Memory Search Workflow
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**3-Layer Pattern (ALWAYS follow this):**
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1. **Search** - Get index of results with IDs
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\`search(query="...", limit=20, project="...")\`
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Returns: Table with IDs, titles, dates (~50-100 tokens/result)
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2. **Timeline** - Get context around interesting results
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\`timeline(anchor=<ID>, depth_before=3, depth_after=3)\`
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Returns: Chronological context showing what was happening
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3. **Fetch** - Get full details ONLY for relevant IDs
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\`get_observations(ids=[...])\` # ALWAYS batch for 2+ items
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Returns: Complete details (~500-1000 tokens/result)
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**Why:** 10x token savings. Never fetch full details without filtering first.`
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}]
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})
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},
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{
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name: 'search',
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description: 'Step 1: Search memory. Returns index with IDs. Params: query, limit, project, type, obs_type, dateStart, dateEnd, offset, orderBy',
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inputSchema: {
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type: 'object',
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properties: {},
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additionalProperties: true
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},
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handler: async (args: any) => {
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const endpoint = TOOL_ENDPOINT_MAP['search'];
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return await callWorkerAPI(endpoint, args);
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}
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},
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{
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name: 'timeline',
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description: 'Step 2: Get context around results. Params: anchor (observation ID) OR query (finds anchor automatically), depth_before, depth_after, project',
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inputSchema: {
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type: 'object',
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properties: {},
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additionalProperties: true
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},
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handler: async (args: any) => {
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const endpoint = TOOL_ENDPOINT_MAP['timeline'];
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return await callWorkerAPI(endpoint, args);
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}
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},
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{
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name: 'get_observations',
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description: 'Step 3: Fetch full details for filtered IDs. Params: ids (array of observation IDs, required), orderBy, limit, project',
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inputSchema: {
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type: 'object',
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properties: {
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ids: {
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type: 'array',
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items: { type: 'number' },
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description: 'Array of observation IDs to fetch (required)'
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}
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},
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required: ['ids'],
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additionalProperties: true
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},
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handler: async (args: any) => {
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return await callWorkerAPIPost('/api/observations/batch', args);
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}
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},
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{
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name: 'save_memory',
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description: 'Save a manual memory/observation for semantic search. Use this to remember important information.',
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inputSchema: {
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type: 'object',
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properties: {
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text: {
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type: 'string',
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description: 'Content to remember (required)'
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},
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title: {
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type: 'string',
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description: 'Short title (auto-generated from text if omitted)'
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},
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project: {
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type: 'string',
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description: 'Project name (uses "claude-mem" if omitted)'
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}
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},
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required: ['text']
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},
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handler: async (args: any) => {
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return await callWorkerAPIPost('/api/memory/save', args);
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}
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}
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];
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// Create the MCP server
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const server = new Server(
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{
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name: 'mcp-search-server',
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version: packageVersion,
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},
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{
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capabilities: {
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tools: {}, // Exposes tools capability (handled by ListToolsRequestSchema and CallToolRequestSchema)
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},
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}
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);
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// Register tools/list handler
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server.setRequestHandler(ListToolsRequestSchema, async () => {
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return {
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tools: tools.map(tool => ({
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name: tool.name,
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description: tool.description,
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inputSchema: tool.inputSchema
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}))
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};
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});
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// Register tools/call handler
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server.setRequestHandler(CallToolRequestSchema, async (request) => {
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const tool = tools.find(t => t.name === request.params.name);
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if (!tool) {
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throw new Error(`Unknown tool: ${request.params.name}`);
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}
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try {
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return await tool.handler(request.params.arguments || {});
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} catch (error) {
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logger.error('SYSTEM', 'Tool execution failed', { tool: request.params.name }, error as Error);
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return {
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content: [{
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type: 'text' as const,
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text: `Tool execution failed: ${error instanceof Error ? error.message : String(error)}`
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}],
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isError: true
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};
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}
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});
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// Cleanup function
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async function cleanup() {
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logger.info('SYSTEM', 'MCP server shutting down');
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process.exit(0);
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}
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// Register cleanup handlers for graceful shutdown
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process.on('SIGTERM', cleanup);
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process.on('SIGINT', cleanup);
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// Start the server
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async function main() {
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// Start the MCP server
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const transport = new StdioServerTransport();
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await server.connect(transport);
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logger.info('SYSTEM', 'Claude-mem search server started');
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// Check Worker availability in background
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setTimeout(async () => {
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const workerAvailable = await verifyWorkerConnection();
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if (!workerAvailable) {
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logger.error('SYSTEM', 'Worker not available', undefined, { workerUrl: WORKER_BASE_URL });
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logger.error('SYSTEM', 'Tools will fail until Worker is started');
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logger.error('SYSTEM', 'Start Worker with: npm run worker:restart');
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} else {
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logger.info('SYSTEM', 'Worker available', undefined, { workerUrl: WORKER_BASE_URL });
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}
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}, 0);
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}
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main().catch((error) => {
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logger.error('SYSTEM', 'Fatal error', undefined, error);
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// Exit gracefully: Windows Terminal won't keep tab open on exit 0
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// The wrapper/plugin will handle restart logic if needed
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process.exit(0);
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});
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