Letta
An MCP server implementation that enables interaction with the Letta API for managing agents, memory blocks, and tools in the Letta system.
What is Letta?
Letta is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to mcp server implementation that enables interaction with the letta api for managing agents, memory blocks, and tools in the letta system.
An MCP server implementation that enables interaction with the Letta API for managing agents, memory blocks, and tools in the Letta system.
This server falls under the Coding Agents category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- An MCP server implementation that enables interaction with t
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx letta-mcp-serverConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Letta
The Letta MCP Server is a high-performance Rust implementation that gives MCP clients full control over a Letta AI instance, exposing 103 operations across 7 consolidated tools for managing agents, memory blocks, archival storage, tools, data sources, jobs, and MCP server lifecycle. It runs with less than 10–30 MB of memory and starts in under 500 ms, making it suitable for both local Claude Desktop setups and production HTTP deployments. Teams building multi-agent systems with Letta use it to let Claude orchestrate agent creation, memory updates, and conversation management through natural language.
Prerequisites
- A running Letta AI instance (self-hosted or cloud) accessible at a known URL and port (default 8283)
- The Letta API password for your instance
- Node.js 18+ installed if using npm install method, or Docker for the container approach
- An MCP client such as Claude Desktop, Cursor, or any stdio/HTTP MCP-compatible tool
Install the Letta MCP server via npm
The npm package installs the correct pre-compiled Rust binary for your platform automatically — no Rust toolchain needed.
npm install -g letta-mcp-serverConfigure Claude Desktop with stdio transport
Add the server to your claude_desktop_config.json, pointing it at your Letta instance URL and providing the password. The default transport is stdio, which is correct for Claude Desktop.
{
"mcpServers": {
"letta": {
"command": "letta-mcp-server",
"args": [],
"env": {
"LETTA_BASE_URL": "http://localhost:8283",
"LETTA_PASSWORD": "your-letta-password"
}
}
}
}Or deploy via Docker for HTTP transport
For production deployments or multi-client access, run the server as a Docker container exposing port 6507 with HTTP transport.
docker run -d \
-p 6507:6507 \
-e LETTA_BASE_URL=http://your-letta-instance:8283 \
-e LETTA_PASSWORD=your-password \
-e TRANSPORT=http \
--name letta-mcp \
ghcr.io/oculairmedia/letta-mcp-server-rust:rust-latestRestart Claude Desktop and verify connectivity
Restart Claude Desktop to load the new server config. Ask the assistant to list available Letta agents to confirm the connection is working.
Optional: Tune response size limits
Set environment variables to control how much data is returned per tool call to manage LLM context usage. The server applies 68–96% size reductions by default.
# Optional tuning environment variables:
# LETTA_MCP_MAX_VALUE_LEN=500 (default: 500 chars for block/passage values)
# LETTA_MCP_CORE_MEMORY_PREVIEW_LEN=200 (default: 200 chars for memory previews)Letta Examples
Client configuration
Connect Claude Desktop to a local Letta instance using stdio transport with the npm-installed binary.
{
"mcpServers": {
"letta": {
"command": "letta-mcp-server",
"args": [],
"env": {
"LETTA_BASE_URL": "http://localhost:8283",
"LETTA_PASSWORD": "your-letta-password",
"RUST_LOG": "info"
}
}
}
}Prompts to try
Use these prompts to manage your Letta agents and memory through Claude.
- "List all agents in my Letta instance"
- "Create a new Letta agent named 'ResearchBot' with a customer support persona"
- "Send the message 'What is the status of order 1234?' to agent ID agent_abc123"
- "Show me the core memory blocks for agent agent_abc123"
- "Search archival memory for passages related to 'quarterly report'"
- "List all tools attached to agent agent_abc123 and add the web_search tool"Troubleshooting Letta
Connection refused when starting: cannot reach LETTA_BASE_URL
Verify your Letta instance is running and accessible at the URL specified in LETTA_BASE_URL. Test with `curl http://localhost:8283/health` from the machine running the MCP server. Update the URL if Letta is running on a different host or port.
Authentication error 401 from Letta API
Double-check the LETTA_PASSWORD value matches the password configured in your Letta instance. For Letta Cloud, use the API key from your account dashboard rather than a password.
letta-mcp-server command not found after npm install
Ensure npm global bin directory is in your PATH. Run `npm bin -g` to find the directory and add it to your PATH, or use npx: replace the command with 'npx' and args with ['letta-mcp-server'].
Frequently Asked Questions about Letta
What is Letta?
Letta is a Model Context Protocol (MCP) server that mcp server implementation that enables interaction with the letta api for managing agents, memory blocks, and tools in the letta system. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Letta?
Follow the installation instructions on the Letta GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Letta?
Letta works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Letta free to use?
Yes, Letta is open source and available under the MIT License license. You can use it freely in both personal and commercial projects.
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Set Up Letta in Your Editor
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Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
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