Central-Memory-MCP

# Central Memory MCP Server [](https://archestra.ai/mcp-catalog/mwgmorningwood__central-memory-mcp) Model Context Protocol (MCP) memory server built with Azure Functions and TypeScript, providing persistent knowledge graph storage for AI assistants in VS Code. Inspired by and forked from [`@modelcontextprotocol/server-memory`](https://github.com/modelcontextprotocol/servers/tree/main/src/memory) ## 🚀 Quick Start ```bash npm install func start ``` ### VS Code Integration 1. **Install recommended extensions** from `.vscode/extensions.json` 2. **MCP configuration** is ready in `.vscode/mcp.json` 3. **Use `#memory-test` tools** in VS Code Copilot chat > **Note**: All MCP tools now use object parameters instead of JSON strings for better type safety and ease of use. ### Test the Server ```bash # Health check curl http://localhost:7071/api/health # Use in VS Code Copilot with object parameters: # #memory-test_create_entities # #memory-test_read_graph # #memory-test_search_entities ``` ### Example Usage in VS Code Copilot **Recommended workflow for best results:** ```text 1. First, check existing data: #memory-test_read_graph workspaceId="my-project" 2. Search for existing entities: #memory-test_search_entities workspaceId="my-project" name="Alice" 3. Create entities (auto-updates existing ones): #memory-test_create_entities workspaceId="my-project" entities={"name": "Alice", "entityType": "Person", "observations": ["Software engineer"]} 4. Create relationships (auto-creates missing entities): #memory-test_create_relations workspaceId="my-project" relations={"from": "Alice", "to": "React Project", "relationType": "worksOn"} 5. Add observations (auto-creates entity if missing): #memory-test_add_observation workspaceId="my-project" entityName="Alice" observation="Leads the frontend team" entityType="Person" ``` **Key Features for Better LLM Usability:** - ✅ Auto-creation of missing entities when adding observations or relations - ✅ Helpful error messages with examples when validation fails - ✅ Workflow guidance to view graph first, then search, then create - ✅ Clear parameter descriptions with expected formats - ✅ Reduced friction - tools handle common edge cases automatically ## 🔧 MCP Tools **Core Operations:** - `read_graph` - **RECOMMENDED FIRST STEP**: View the entire knowledge graph to understand existing data - `create_entities` - Create entities with auto-update of existing ones - `create_relations` - Create relationships with auto-creation of missing entities - `search_entities` / `search_relations` - Search and verify existing data - `add_observation` - Add observations with auto-creation of missing entities - `update_entity` - Update entity observations and metadata - `delete_entity` - Remove entity and all its relations - `get_stats` - Get workspace statistics - `clear_memory` - Clear all workspace data **Recommended Workflow:** 1. Use `read_graph` to understand existing data 2. Use `search_entities` to check for existing entities 3. Use `create_entities` to add new entities 4. Use `create_relations` to connect entities 5. Use `add_observation` to add new information **Advanced Features:** - `get_temporal_events` - Time-based activity tracking - `merge_entities` - Merge duplicate entities - `detect_duplicate_entities` - Find potential duplicates - `execute_batch_operations` - Batch multiple operations - `get_user_stats` - Get user-specific statistics - `search_relations_by_user` - Find relations by user ## 🏗️ Architecture Built with: - **Azure Functions v4** with TypeScript - **Azure Table Storage** for persistent data (via Azurite locally) - **Model Context Protocol (MCP)** for VS Code integration - **Workspace isolation** - each project gets separate storage ## � Project Structure ```text src/ ├── functions/ # Azure Functions endpoints ├── services/ # Business logic (storage, entities, relations) ├── types/ # TypeScript definitions └── index.ts # Main entry point ``` ## 📚 Documentation For detailed information, see the `.docs/` folder: - **[Architecture Guide](.docs/ARCHITECTURE.md)** - Technical design and patterns - **[API Reference](.docs/API.md)** - Complete endpoint documentation - **[Storage Guide](.docs/STORAGE.md)** - Storage configuration and workspace management - **[Deployment Guide](.docs/DEPLOYMENT.md)** - Production deployment options ## 🔒 Production Notes - Uses Azure Table Storage with managed identity for security - Workspace isolation prevents data leakage between projects - Health endpoints for monitoring and container orchestration - Automatic fallback to local storage for development ## 📝 License MIT License - see LICENSE file for details.