Central Memory MCP Server

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

🚀 Quick Start

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

# 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:

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

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 - Technical design and patterns
• API Reference - Complete endpoint documentation
• Storage Guide - Storage configuration and workspace management
• Deployment Guide - 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.