61a4050a8e
Implementation Summary:
- REST API with FastAPI (complete CRUD operations)
- MCP Server with Python MCP SDK (7 tools)
- Supabase migrations (pgvector setup)
- Docker Compose orchestration
- Mintlify documentation site
- Environment configuration
- Shared config module
REST API Features:
- POST /v1/memories/ - Add memory
- GET /v1/memories/search - Semantic search
- GET /v1/memories/{id} - Get memory
- GET /v1/memories/user/{user_id} - User memories
- PATCH /v1/memories/{id} - Update memory
- DELETE /v1/memories/{id} - Delete memory
- GET /v1/health - Health check
- GET /v1/stats - Statistics
- Bearer token authentication
- OpenAPI documentation
MCP Server Tools:
- add_memory - Add from messages
- search_memories - Semantic search
- get_memory - Retrieve by ID
- get_all_memories - List all
- update_memory - Update content
- delete_memory - Delete by ID
- delete_all_memories - Bulk delete
Infrastructure:
- Neo4j 5.26 with APOC/GDS
- Supabase pgvector integration
- Docker network: localai
- Health checks and monitoring
- Structured logging
Documentation:
- Introduction page
- Quickstart guide
- Architecture deep dive
- Mintlify configuration
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
344 lines
13 KiB
Python
344 lines
13 KiB
Python
"""
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MCP tools for T6 Mem0 v2
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Tool definitions and handlers
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"""
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import logging
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from typing import Any, Dict, List
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from mcp.types import Tool, TextContent
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from mem0 import Memory
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logger = logging.getLogger(__name__)
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class MemoryTools:
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"""MCP tools for memory operations"""
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def __init__(self, memory: Memory):
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"""
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Initialize memory tools
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Args:
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memory: Mem0 instance
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"""
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self.memory = memory
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def get_tool_definitions(self) -> List[Tool]:
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"""
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Get MCP tool definitions
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Returns:
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List of Tool definitions
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"""
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return [
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Tool(
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name="add_memory",
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description="Add new memory from messages. Extracts and stores important information from conversation.",
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inputSchema={
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"type": "object",
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"properties": {
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"messages": {
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"type": "array",
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"items": {
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"type": "object",
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"properties": {
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"role": {"type": "string", "enum": ["user", "assistant", "system"]},
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"content": {"type": "string"}
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},
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"required": ["role", "content"]
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},
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"description": "Conversation messages to extract memory from"
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},
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"user_id": {
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"type": "string",
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"description": "User identifier (optional)"
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},
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"agent_id": {
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"type": "string",
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"description": "Agent identifier (optional)"
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},
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"metadata": {
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"type": "object",
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"description": "Additional metadata (optional)"
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}
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},
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"required": ["messages"]
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}
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),
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Tool(
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name="search_memories",
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description="Search memories by semantic similarity. Find relevant memories based on a query.",
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inputSchema={
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"type": "object",
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"properties": {
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"query": {
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"type": "string",
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"description": "Search query"
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},
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"user_id": {
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"type": "string",
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"description": "Filter by user ID (optional)"
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},
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"agent_id": {
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"type": "string",
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"description": "Filter by agent ID (optional)"
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},
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"limit": {
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"type": "integer",
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"minimum": 1,
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"maximum": 50,
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"default": 10,
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"description": "Maximum number of results"
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}
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},
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"required": ["query"]
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}
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),
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Tool(
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name="get_memory",
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description="Get a specific memory by its ID",
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inputSchema={
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"type": "object",
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"properties": {
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"memory_id": {
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"type": "string",
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"description": "Memory identifier"
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}
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},
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"required": ["memory_id"]
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}
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),
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Tool(
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name="get_all_memories",
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description="Get all memories for a user or agent",
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inputSchema={
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"type": "object",
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"properties": {
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"user_id": {
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"type": "string",
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"description": "User identifier (optional)"
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},
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"agent_id": {
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"type": "string",
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"description": "Agent identifier (optional)"
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}
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}
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}
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),
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Tool(
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name="update_memory",
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description="Update an existing memory's content",
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inputSchema={
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"type": "object",
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"properties": {
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"memory_id": {
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"type": "string",
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"description": "Memory identifier"
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},
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"data": {
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"type": "string",
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"description": "New memory content"
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}
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},
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"required": ["memory_id", "data"]
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}
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),
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Tool(
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name="delete_memory",
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description="Delete a specific memory by ID",
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inputSchema={
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"type": "object",
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"properties": {
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"memory_id": {
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"type": "string",
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"description": "Memory identifier"
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}
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},
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"required": ["memory_id"]
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}
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),
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Tool(
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name="delete_all_memories",
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description="Delete all memories for a user or agent. Use with caution!",
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inputSchema={
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"type": "object",
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"properties": {
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"user_id": {
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"type": "string",
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"description": "User identifier (optional)"
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},
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"agent_id": {
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"type": "string",
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"description": "Agent identifier (optional)"
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}
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}
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}
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)
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]
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async def handle_add_memory(self, arguments: Dict[str, Any]) -> List[TextContent]:
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"""Handle add_memory tool call"""
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try:
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messages = arguments.get("messages", [])
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user_id = arguments.get("user_id")
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agent_id = arguments.get("agent_id")
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metadata = arguments.get("metadata", {})
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result = self.memory.add(
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messages=messages,
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user_id=user_id,
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agent_id=agent_id,
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metadata=metadata
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)
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memories = result.get('results', [])
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response = f"Successfully added {len(memories)} memory(ies):\n\n"
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for mem in memories:
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response += f"- {mem.get('memory', mem.get('data', 'N/A'))}\n"
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response += f" ID: {mem.get('id', 'N/A')}\n\n"
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return [TextContent(type="text", text=response)]
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except Exception as e:
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logger.error(f"Error adding memory: {e}")
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return [TextContent(type="text", text=f"Error: {str(e)}")]
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async def handle_search_memories(self, arguments: Dict[str, Any]) -> List[TextContent]:
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"""Handle search_memories tool call"""
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try:
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query = arguments.get("query")
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user_id = arguments.get("user_id")
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agent_id = arguments.get("agent_id")
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limit = arguments.get("limit", 10)
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memories = self.memory.search(
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query=query,
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user_id=user_id,
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agent_id=agent_id,
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limit=limit
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)
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if not memories:
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return [TextContent(type="text", text="No memories found matching your query.")]
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response = f"Found {len(memories)} relevant memory(ies):\n\n"
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for i, mem in enumerate(memories, 1):
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response += f"{i}. {mem.get('memory', mem.get('data', 'N/A'))}\n"
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response += f" ID: {mem.get('id', 'N/A')}\n"
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if 'score' in mem:
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response += f" Relevance: {mem['score']:.2%}\n"
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response += "\n"
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return [TextContent(type="text", text=response)]
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except Exception as e:
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logger.error(f"Error searching memories: {e}")
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return [TextContent(type="text", text=f"Error: {str(e)}")]
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async def handle_get_memory(self, arguments: Dict[str, Any]) -> List[TextContent]:
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"""Handle get_memory tool call"""
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try:
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memory_id = arguments.get("memory_id")
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memory = self.memory.get(memory_id=memory_id)
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if not memory:
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return [TextContent(type="text", text=f"Memory not found: {memory_id}")]
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response = f"Memory Details:\n\n"
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response += f"ID: {memory.get('id', 'N/A')}\n"
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response += f"Content: {memory.get('memory', memory.get('data', 'N/A'))}\n"
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if memory.get('user_id'):
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response += f"User ID: {memory['user_id']}\n"
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if memory.get('agent_id'):
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response += f"Agent ID: {memory['agent_id']}\n"
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if memory.get('metadata'):
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response += f"Metadata: {memory['metadata']}\n"
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return [TextContent(type="text", text=response)]
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except Exception as e:
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logger.error(f"Error getting memory: {e}")
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return [TextContent(type="text", text=f"Error: {str(e)}")]
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async def handle_get_all_memories(self, arguments: Dict[str, Any]) -> List[TextContent]:
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"""Handle get_all_memories tool call"""
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try:
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user_id = arguments.get("user_id")
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agent_id = arguments.get("agent_id")
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memories = self.memory.get_all(
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user_id=user_id,
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agent_id=agent_id
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)
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if not memories:
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return [TextContent(type="text", text="No memories found.")]
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response = f"Retrieved {len(memories)} memory(ies):\n\n"
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for i, mem in enumerate(memories, 1):
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response += f"{i}. {mem.get('memory', mem.get('data', 'N/A'))}\n"
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response += f" ID: {mem.get('id', 'N/A')}\n\n"
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return [TextContent(type="text", text=response)]
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except Exception as e:
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logger.error(f"Error getting all memories: {e}")
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return [TextContent(type="text", text=f"Error: {str(e)}")]
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async def handle_update_memory(self, arguments: Dict[str, Any]) -> List[TextContent]:
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"""Handle update_memory tool call"""
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try:
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memory_id = arguments.get("memory_id")
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data = arguments.get("data")
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result = self.memory.update(
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memory_id=memory_id,
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data=data
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)
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response = f"Memory updated successfully:\n\n"
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response += f"ID: {result.get('id', memory_id)}\n"
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response += f"New Content: {data}\n"
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return [TextContent(type="text", text=response)]
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except Exception as e:
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logger.error(f"Error updating memory: {e}")
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return [TextContent(type="text", text=f"Error: {str(e)}")]
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async def handle_delete_memory(self, arguments: Dict[str, Any]) -> List[TextContent]:
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"""Handle delete_memory tool call"""
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try:
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memory_id = arguments.get("memory_id")
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self.memory.delete(memory_id=memory_id)
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return [TextContent(type="text", text=f"Memory {memory_id} deleted successfully.")]
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except Exception as e:
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logger.error(f"Error deleting memory: {e}")
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return [TextContent(type="text", text=f"Error: {str(e)}")]
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async def handle_delete_all_memories(self, arguments: Dict[str, Any]) -> List[TextContent]:
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"""Handle delete_all_memories tool call"""
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try:
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user_id = arguments.get("user_id")
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agent_id = arguments.get("agent_id")
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self.memory.delete_all(
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user_id=user_id,
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agent_id=agent_id
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)
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filter_str = f"user_id={user_id}" if user_id else f"agent_id={agent_id}" if agent_id else "all filters"
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return [TextContent(type="text", text=f"All memories deleted for {filter_str}.")]
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except Exception as e:
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logger.error(f"Error deleting all memories: {e}")
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return [TextContent(type="text", text=f"Error: {str(e)}")]
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