Add MCP HTTP/SSE server and complete n8n integration
Major Changes: - Implemented MCP HTTP/SSE transport server for n8n and web clients - Created mcp_server/http_server.py with FastAPI for JSON-RPC 2.0 over HTTP - Added health check endpoint (/health) for container monitoring - Refactored mcp-server/ to mcp_server/ (Python module structure) - Updated Dockerfile.mcp to run HTTP server with health checks MCP Server Features: - 7 memory tools exposed via MCP (add, search, get, update, delete) - HTTP/SSE transport on port 8765 for n8n integration - stdio transport for Claude Code integration - JSON-RPC 2.0 protocol implementation - CORS support for web clients n8n Integration: - Successfully tested with AI Agent workflows - MCP Client Tool configuration documented - Working webhook endpoint tested and verified - System prompt optimized for automatic user_id usage Documentation: - Created comprehensive Mintlify documentation site - Added docs/mcp/introduction.mdx - MCP server overview - Added docs/mcp/installation.mdx - Installation guide - Added docs/mcp/tools.mdx - Complete tool reference - Added docs/examples/n8n.mdx - n8n integration guide - Added docs/examples/claude-code.mdx - Claude Code setup - Updated README.md with MCP HTTP server info - Updated roadmap to mark Phase 1 as complete Bug Fixes: - Fixed synchronized delete operations across Supabase and Neo4j - Updated memory_service.py with proper error handling - Fixed Neo4j connection issues in delete operations Configuration: - Added MCP_HOST and MCP_PORT environment variables - Updated .env.example with MCP server configuration - Updated docker-compose.yml with MCP container health checks Testing: - Added test scripts for MCP HTTP endpoint verification - Created test workflows in n8n - Verified all 7 memory tools working correctly - Tested synchronized operations across both stores Version: 1.0.0 Status: Phase 1 Complete - Production Ready 🤖 Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
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Claude Code
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---
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title: 'Claude Code Integration'
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description: 'Use T6 Mem0 v2 with Claude Code for AI-powered development'
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---
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# Claude Code Integration
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Integrate the T6 Mem0 v2 MCP server with Claude Code to give your AI coding assistant persistent memory across sessions.
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## Prerequisites
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- Claude Code CLI installed
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- T6 Mem0 v2 MCP server installed locally
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- Python 3.11+ environment
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- Running Supabase and Neo4j instances
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## Installation
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### 1. Install Dependencies
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```bash
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cd /path/to/t6_mem0_v2
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pip install -r requirements.txt
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```
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### 2. Configure Environment
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Create `.env` file with required credentials:
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```bash
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# OpenAI
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OPENAI_API_KEY=your_openai_key_here
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# Supabase (Vector Store)
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SUPABASE_CONNECTION_STRING=postgresql://user:pass@host:port/database
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# Neo4j (Graph Store)
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NEO4J_URI=neo4j://localhost:7687
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NEO4J_USER=neo4j
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NEO4J_PASSWORD=your_neo4j_password
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# Mem0 Configuration
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MEM0_COLLECTION_NAME=t6_memories
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MEM0_EMBEDDING_DIMS=1536
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MEM0_VERSION=v1.1
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```
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### 3. Verify MCP Server
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Test the stdio transport:
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```bash
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echo '{"jsonrpc":"2.0","id":1,"method":"tools/list","params":{}}' | python -m mcp_server.main
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```
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Expected output:
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```json
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{
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"jsonrpc": "2.0",
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"id": 1,
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"result": {
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"tools": [
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{"name": "add_memory", "description": "Add new memory from messages..."},
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{"name": "search_memories", "description": "Search memories by semantic similarity..."},
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...
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]
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}
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}
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```
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## Claude Code Configuration
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### Option 1: MCP Server Configuration (Recommended)
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Add to your Claude Code MCP settings file (`~/.config/claude/mcp.json`):
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```json
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{
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"mcpServers": {
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"t6-mem0": {
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"command": "python",
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"args": ["-m", "mcp_server.main"],
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"cwd": "/path/to/t6_mem0_v2",
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"env": {
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"OPENAI_API_KEY": "${OPENAI_API_KEY}",
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"SUPABASE_CONNECTION_STRING": "${SUPABASE_CONNECTION_STRING}",
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"NEO4J_URI": "neo4j://localhost:7687",
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"NEO4J_USER": "neo4j",
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"NEO4J_PASSWORD": "${NEO4J_PASSWORD}",
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"MEM0_COLLECTION_NAME": "t6_memories",
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"MEM0_EMBEDDING_DIMS": "1536",
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"MEM0_VERSION": "v1.1"
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}
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}
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}
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}
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```
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### Option 2: Direct Python Integration
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Use the MCP SDK directly in Python:
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```python
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from mcp import ClientSession, StdioServerParameters
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from mcp.client.stdio import stdio_client
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# Configure server
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server_params = StdioServerParameters(
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command="python",
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args=["-m", "mcp_server.main"],
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env={
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"OPENAI_API_KEY": "your_key_here",
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"SUPABASE_CONNECTION_STRING": "postgresql://...",
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"NEO4J_URI": "neo4j://localhost:7687",
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"NEO4J_USER": "neo4j",
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"NEO4J_PASSWORD": "your_password"
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}
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)
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# Connect and use
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async with stdio_client(server_params) as (read, write):
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async with ClientSession(read, write) as session:
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# Initialize session
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await session.initialize()
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# List available tools
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tools = await session.list_tools()
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print(f"Available tools: {[tool.name for tool in tools.tools]}")
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# Add a memory
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result = await session.call_tool(
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"add_memory",
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arguments={
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"messages": [
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{"role": "user", "content": "I prefer TypeScript over JavaScript"},
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{"role": "assistant", "content": "Got it, I'll remember that!"}
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],
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"user_id": "developer_123"
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}
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)
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# Search memories
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results = await session.call_tool(
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"search_memories",
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arguments={
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"query": "What languages does the developer prefer?",
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"user_id": "developer_123",
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"limit": 5
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}
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)
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```
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## Usage Examples
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### Example 1: Storing Code Preferences
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```python
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# User tells Claude Code their preferences
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User: "I prefer using async/await over callbacks in JavaScript"
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# Claude Code automatically calls add_memory
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await session.call_tool(
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"add_memory",
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arguments={
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"messages": [
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{
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"role": "user",
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"content": "I prefer using async/await over callbacks in JavaScript"
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},
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{
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"role": "assistant",
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"content": "I'll remember your preference for async/await!"
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}
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],
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"user_id": "developer_123",
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"metadata": {
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"category": "coding_preference",
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"language": "javascript"
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}
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}
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)
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```
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### Example 2: Recalling Project Context
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```python
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# Later in a new session
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User: "How should I structure this async function?"
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# Claude Code searches memories first
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memories = await session.call_tool(
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"search_memories",
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arguments={
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"query": "JavaScript async preferences",
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"user_id": "developer_123",
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"limit": 3
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}
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)
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# Claude uses retrieved context to provide personalized response
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# "Based on your preference for async/await, here's how I'd structure it..."
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```
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### Example 3: Project-Specific Memory
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```python
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# Store project-specific information
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await session.call_tool(
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"add_memory",
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arguments={
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"messages": [
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{
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"role": "user",
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"content": "This project uses Supabase for the database and Neo4j for the knowledge graph"
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},
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{
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"role": "assistant",
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"content": "Got it! I'll remember the tech stack for this project."
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}
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],
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"user_id": "developer_123",
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"agent_id": "project_t6_mem0",
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"metadata": {
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"project": "t6_mem0_v2",
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"category": "tech_stack"
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}
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}
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)
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```
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## Available Tools in Claude Code
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Once configured, these tools are automatically available:
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| Tool | Description | Use Case |
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|------|-------------|----------|
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| `add_memory` | Store information | Save preferences, project details, learned patterns |
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| `search_memories` | Semantic search | Find relevant context from past conversations |
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| `get_all_memories` | Get all memories | Review everything Claude knows about you |
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| `update_memory` | Modify memory | Correct or update stored information |
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| `delete_memory` | Remove specific memory | Clear outdated information |
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| `delete_all_memories` | Clear all memories | Start fresh for new project |
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## Best Practices
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### 1. Use Meaningful User IDs
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```python
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# Good - descriptive IDs
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user_id = "developer_john_doe"
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agent_id = "project_ecommerce_backend"
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# Avoid - generic IDs
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user_id = "user1"
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agent_id = "agent"
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```
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### 2. Add Rich Metadata
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```python
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metadata = {
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"project": "t6_mem0_v2",
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"category": "bug_fix",
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"file": "mcp_server/http_server.py",
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"timestamp": "2025-10-15T10:30:00Z",
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"session_id": "abc-123-def"
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}
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```
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### 3. Search Before Adding
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```python
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# Check if information already exists
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existing = await session.call_tool(
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"search_memories",
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arguments={
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"query": "Python coding style preferences",
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"user_id": "developer_123"
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}
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)
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# Only add if not found or needs updating
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if not existing or needs_update:
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await session.call_tool("add_memory", ...)
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```
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### 4. Regular Cleanup
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```python
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# Periodically clean up old project memories
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await session.call_tool(
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"delete_all_memories",
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arguments={
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"agent_id": "old_project_archived"
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}
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)
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```
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## Troubleshooting
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### MCP Server Won't Start
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**Error**: `ModuleNotFoundError: No module named 'mcp_server'`
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**Solution**: Ensure you're running from the correct directory:
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```bash
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cd /path/to/t6_mem0_v2
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python -m mcp_server.main
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```
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### Database Connection Errors
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**Error**: `Cannot connect to Supabase/Neo4j`
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**Solution**: Verify services are running and credentials are correct:
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```bash
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# Test Neo4j
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curl http://localhost:7474
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# Test Supabase connection
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psql $SUPABASE_CONNECTION_STRING -c "SELECT 1"
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```
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### Environment Variables Not Loading
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**Error**: `KeyError: 'OPENAI_API_KEY'`
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**Solution**: Load `.env` file or set environment variables:
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```bash
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# Load from .env
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export $(cat .env | xargs)
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# Or set directly
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export OPENAI_API_KEY=your_key_here
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```
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### Slow Response Times
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**Issue**: Tool calls taking longer than expected
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**Solutions**:
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- Check network latency to Supabase
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- Verify Neo4j indexes are created
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- Reduce `limit` parameter in search queries
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- Consider caching frequently accessed memories
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## Advanced Usage
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### Custom Memory Categories
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```python
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# Define custom categories
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CATEGORIES = {
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"preferences": "User coding preferences and style",
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"bugs": "Known bugs and their solutions",
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"architecture": "System design decisions",
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"dependencies": "Project dependencies and versions"
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}
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# Store with category
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await session.call_tool(
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"add_memory",
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arguments={
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"messages": [...],
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"metadata": {
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"category": "architecture",
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"importance": "high"
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}
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}
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)
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```
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### Multi-Agent Collaboration
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```python
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# Different agents for different purposes
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AGENTS = {
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"code_reviewer": "Reviews code for best practices",
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"debugger": "Helps debug issues",
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"architect": "Provides architectural guidance"
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}
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# Store agent-specific knowledge
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await session.call_tool(
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"add_memory",
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arguments={
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"messages": [...],
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"user_id": "developer_123",
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"agent_id": "code_reviewer",
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"metadata": {"role": "code_review"}
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}
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)
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```
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### Session Management
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```python
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import uuid
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from datetime import datetime
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# Create session tracking
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session_id = str(uuid.uuid4())
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session_start = datetime.now().isoformat()
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# Store with session context
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metadata = {
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"session_id": session_id,
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"session_start": session_start,
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"context": "debugging_authentication"
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}
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```
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## Next Steps
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<CardGroup cols={2}>
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<Card title="Tool Reference" icon="wrench" href="/mcp/tools">
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Complete reference for all 7 MCP tools
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</Card>
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<Card title="n8n Integration" icon="workflow" href="/examples/n8n">
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Use MCP in n8n workflows
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</Card>
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</CardGroup>
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Reference in New Issue
Block a user