MCP-Mem0: Long-Term Memory for AI Agents

What is MCP-Mem0?

MCP-Mem0 is a template implementation of the Model Context Protocol (MCP) server integrated with Mem0, designed to provide AI agents with persistent memory capabilities.

How to use MCP-Mem0?

To use MCP-Mem0, clone the repository, install the necessary dependencies, configure your environment variables, and run the server using either uv or Docker.

Key features of MCP-Mem0?

• save_memory: Store information in long-term memory with semantic indexing.
• get_all_memories: Retrieve all stored memories for comprehensive context.
• search_memories: Find relevant memories using semantic search.

Use cases of MCP-Mem0?

1. Enabling AI agents to remember user interactions over time.
2. Assisting in complex decision-making by recalling past experiences.
3. Providing context-aware responses in conversational AI applications.

FAQ from MCP-Mem0?

• Can MCP-Mem0 be used with any AI model?

Yes! MCP-Mem0 can integrate with various LLM providers like OpenAI, OpenRouter, or Ollama.

• Is MCP-Mem0 free to use?

Yes! MCP-Mem0 is open-source and free to use under the MIT license.

• What are the prerequisites for running MCP-Mem0?

You need Python 3.12+, a PostgreSQL database, and API keys for your chosen LLM provider.