MCP-Mem0: Long-Term Memory for AI Agents

Created By
gustavoserafima year ago
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?

  1. Enabling AI agents to remember user interactions over time.
  2. Assisting in personalized AI responses based on past interactions.
  3. 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.

Project Info
Created At
a year ago
Updated At
a year ago
Author Name
gustavoserafim
Star
0
Language
Python
License
MIT license

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