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Servidor Letta-MCP
Servidor MCP para administrar el servidor Letta y comunicarse con agentes
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Letta MCP Server
A server that provides tools for agent management, memory operations, and integration with the Letta system.
Quick Setup
Option 1: Run with Node.js
# Development (with hot reload)
npm run dev:sse # SSE transport
# Production
npm run build # Build TypeScript first
npm run start:sse # SSE transport
Option 2: Run with Docker
# Build and run locally
docker build -t letta-mcp-server .
docker run -d -p 3001:3001 -e PORT=3001 -e NODE_ENV=production --name letta-mcp letta-mcp-server
# Or use the public image
docker run -d -p 3001:3001 -e PORT=3001 -e NODE_ENV=production --name letta-mcp ghcr.io/oculairmedia/letta-mcp-server:latest
Directory Structure
- index.js - Main entry point
-
core/
- Core server functionality -
tools/
- Individual tool implementations -
transports/
- Server transport implementations (stdio and SSE)
Available Tools
Agent Management
Tool | Description | Required Parameters | Optional Parameters |
---|---|---|---|
create_agent |
Create a new Letta agent | name, description | model, embedding |
list_agents |
List all available agents | - | filter |
prompt_agent |
Send a message to an agent | agent_id, message | - |
get_agent |
Get agent details by ID | agent_id | - |
modify_agent |
Update an existing agent | agent_id, update_data | - |
delete_agent |
Delete an agent | agent_id | - |
clone_agent |
Clone an existing agent | source_agent_id, new_agent_name | override_existing_tools, project_id |
bulk_delete_agents |
Delete multiple agents | - | agent_ids, agent_name_filter, agent_tag_filter |
Memory Management
Tool | Description | Required Parameters | Optional Parameters |
---|---|---|---|
list_memory_blocks |
List all memory blocks | - | filter, agent_id, page, pageSize, label |
create_memory_block |
Create a new memory block | name, label, value | agent_id, metadata |
read_memory_block |
Read a memory block | block_id | agent_id |
update_memory_block |
Update a memory block | block_id | value, metadata, agent_id |
attach_memory_block |
Attach memory to an agent | block_id, agent_id | label |
Tool Management
Tool | Description | Required Parameters | Optional Parameters |
---|---|---|---|
list_tools |
List all available tools | - | filter, page, pageSize |
list_agent_tools |
List tools for a specific agent | agent_id | - |
attach_tool |
Attach tools to an agent | agent_id | tool_id, tool_ids, tool_names |
upload_tool |
Upload a new tool | name, description, source_code | category, agent_id |
bulk_attach_tool_to_agents |
Attach a tool to multiple agents | tool_id | agent_name_filter, agent_tag_filter |
Additional Tools
-
Model Management:
list_llm_models
,list_embedding_models
-
Archive Management:
list_passages
,create_passage
,modify_passage
,delete_passage
-
MCP Server Management:
list_mcp_servers
,list_mcp_tools_by_server
-
Import/Export:
export_agent
,import_agent
Docker Operations
# View container logs
docker logs -f letta-mcp
# Stop the container
docker stop letta-mcp
# Update to latest version
docker pull ghcr.io/oculairmedia/letta-mcp-server:latest
docker stop letta-mcp
docker rm letta-mcp
docker run -d -p 3001:3001 -e PORT=3001 -e NODE_ENV=production --name letta-mcp ghcr.io/oculairmedia/letta-mcp-server:latest
Configuration with MCP Settings
Add the server to your mcp_settings.json:
"letta": {
"command": "node",
"args": [
"--no-warnings",
"--experimental-modules",
"path/to/letta-server/index.js"
],
"env": {
"LETTA_BASE_URL": "https://your-letta-instance.com",
"LETTA_PASSWORD": "yourPassword"
},
"disabled": false,
"alwaysAllow": [
"upload_tool",
"attach_tool",
"list_agents",
"list_memory_blocks"
],
"timeout": 300
}
For remote instances, use the URL configuration:
"remote_letta_tools": {
"url": "http://your-server:3001/sse",
"disabled": false,
"alwaysAllow": [
"attach_tool",
"list_agents",
"list_tools",
"get_agent"
],
"timeout": 120
}
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Reviews

user_CHYUbzmN
As a loyal user of mcp_server, I must say it has significantly improved my server management experience. The interface is user-friendly, and the performance is top-notch. The detailed documentation provided by karansharma3009 makes setup and maintenance a breeze. Highly recommended for anyone looking to streamline their server operations. Check it out here: https://mcp.so/server/mcp_server/karansharma3009