Overview
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?
- Enabling AI agents to remember user interactions over time.
- Assisting in personalized AI responses based on past interactions.
- Facilitating complex memory management for AI applications.
FAQ from MCP-Mem0?
- Can MCP-Mem0 be used with any AI agent?
Yes! MCP-Mem0 is designed to be compatible with any MCP-compatible client.
- Is there a recommended way to run MCP-Mem0?
Yes! Running MCP-Mem0 using Docker is recommended for ease of setup.
- What are the prerequisites for using MCP-Mem0?
You need Python 3.12+, a PostgreSQL database, and API keys for your chosen LLM provider.
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