What is Memgpt Mcp Server

Memgpt-MCP-Server is a Model Context Protocol (MCP) server built with TypeScript that provides persistent memory and multi-model support for large language models (LLMs). It allows users to chat with various LLM providers while keeping track of conversation history.

Use cases

Use cases for Memgpt-MCP-Server include customer support automation, content moderation, interactive applications, and any scenario requiring conversational AI with memory capabilities. It is suitable for developers looking to integrate LLMs into their applications.

How to use

To use Memgpt-MCP-Server, install the necessary dependencies with ‘npm install’, build the server using ‘npm run build’, and configure it for your environment. You can set up the server configuration for Claude Desktop and specify your API keys for different LLM providers.

Key features

Key features include tools for sending messages to LLM providers, retrieving and clearing conversation history, switching between different LLM providers, and selecting specific models from those providers. It supports multiple providers like OpenAI, Anthropic, OpenRouter, and Ollama.

Where to use

undefined

MemGPT MCP Server

A TypeScript-based MCP server that implements a memory system for LLMs. It provides tools for chatting with different LLM providers while maintaining conversation history.

Features

Tools

• chat - Send a message to the current LLM provider

  • Takes a message parameter
  • Supports multiple providers (OpenAI, Anthropic, OpenRouter, Ollama)

• get_memory - Retrieve conversation history

  • Optional limit parameter to specify number of memories to retrieve
  • Pass limit: null for unlimited memory retrieval
  • Returns memories in chronological order with timestamps

• clear_memory - Clear conversation history

  • Removes all stored memories

• use_provider - Switch between different LLM providers

  • Supports OpenAI, Anthropic, OpenRouter, and Ollama
  • Persists provider selection

• use_model - Switch to a different model for the current provider

  • Supports provider-specific models:
    • Anthropic Claude Models:
      • Claude 3 Series:
        • claude-3-haiku: Fastest response times, ideal for tasks like customer support and content moderation
        • claude-3-sonnet: Balanced performance for general-purpose use
        • claude-3-opus: Advanced model for complex reasoning and high-performance tasks
      • Claude 3.5 Series:
        • claude-3.5-haiku: Enhanced speed and cost-effectiveness
        • claude-3.5-sonnet: Superior performance with computer interaction capabilities
    • OpenAI: ‘gpt-4o’, ‘gpt-4o-mini’, ‘gpt-4-turbo’
    • OpenRouter: Any model in ‘provider/model’ format (e.g., ‘openai/gpt-4’, ‘anthropic/claude-2’)
    • Ollama: Any locally available model (e.g., ‘llama2’, ‘codellama’)
  • Persists model selection

Development

Install dependencies:

npm install

Build the server:

npm run build

For development with auto-rebuild:

npm run watch

Installation

To use with Claude Desktop, add the server config:

On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "letta-memgpt": {
      "command": "/path/to/memgpt-server/build/index.js",
      "env": {
        "OPENAI_API_KEY": "your-openai-key",
        "ANTHROPIC_API_KEY": "your-anthropic-key",
        "OPENROUTER_API_KEY": "your-openrouter-key"
      }
    }
  }
}

Environment Variables

• OPENAI_API_KEY - Your OpenAI API key
• ANTHROPIC_API_KEY - Your Anthropic API key
• OPENROUTER_API_KEY - Your OpenRouter API key

Debugging

Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector:

npm run inspector

The Inspector will provide a URL to access debugging tools in your browser.

Recent Updates

Claude 3 and 3.5 Series Support (March 2024)

• Added support for latest Claude models:
  • Claude 3 Series (Haiku, Sonnet, Opus)
  • Claude 3.5 Series (Haiku, Sonnet)

Unlimited Memory Retrieval

• Added support for retrieving unlimited conversation history
• Use { "limit": null } with the get_memory tool to retrieve all stored memories
• Use { "limit": n } to retrieve the n most recent memories
• Default limit is 10 if not specified