Mem0 MCP Server
by ryaker
A Model Context Protocol (MCP) server for integrating AI assistants with Mem0.ai's persistent memory system. It acts as a bridge between AI models and the Mem0 memory system, enabling assistants to store and retrieve memories.
Last updated: N/A
What is Mem0 MCP Server?
This server provides MCP-compatible tools that let any compatible AI assistant access and manage persistent memories stored in Mem0. It acts as a bridge between AI models and the Mem0 memory system.
How to use Mem0 MCP Server?
The server can be run directly from GitHub using uvx
without needing to clone the repository or install it locally. You need to configure your AI assistant (like Cursor or Claude Desktop) with the path to uvx
and the repository URL. You also need to set the MEM0_API_KEY
environment variable.
Key features of Mem0 MCP Server
Store and retrieve memories
Search memories with semantic similarity
Manage different memory types (episodic, semantic, procedural)
Utilize short-term memory for conversation context
Apply selective memory patterns
Create knowledge graphs from memories
Use cases of Mem0 MCP Server
Enhancing AI assistant memory capabilities
Building AI applications with persistent knowledge
Creating personalized AI experiences
Integrating AI with knowledge graphs
FAQ from Mem0 MCP Server
Do I need to install anything?
Do I need to install anything?
No, the server can be run directly from GitHub using uvx
without needing to clone the repository or install it locally.
How do I configure the server in Cursor or Claude Desktop?
How do I configure the server in Cursor or Claude Desktop?
You need to find the full path to your uvx
executable and add a configuration block to your MCP configuration file, replacing the path with the actual path you found. You also need to set the MEM0_API_KEY
environment variable.
What if I see a mem0ai[neo4j]
warning?
What if I see a mem0ai[neo4j]
warning?
If using the managed Mem0.ai platform, this warning can be safely ignored. If self-hosting Mem0 with Neo4j, you need to ensure the Neo4j-related Python libraries are installed manually.
How do I make it easy for my AI assistant to reference the server's capabilities?
How do I make it easy for my AI assistant to reference the server's capabilities?
You can load the USAGE_GUIDE.md
content into Mem0 by copying the content and asking your AI assistant to add it as a memory. Then, you can retrieve it later using the memory ID.
What memory types are supported?
What memory types are supported?
The server supports short-term memories (Conversation, Working, Attention) and long-term memories (Episodic, Semantic, Procedural).