LM Studio MCP server for AI agents

LMStudio-MCP serves as a bridge between Claude (with Model Control Protocol capabilities) and your locally running LM Studio instance. This allows Claude to interact with your local LLM models, checking their health, listing available models, and generating completions using your private local models rather than Claude's default models.

Installation Options

Quick Installation (Recommended)

The fastest way to install LMStudio-MCP is with the one-line installer:

curl -fsSL https://raw.githubusercontent.com/infinitimeless/LMStudio-MCP/main/install.sh | bash

Manual Installation

Local Python Installation

git clone https://github.com/infinitimeless/LMStudio-MCP.git
cd LMStudio-MCP
pip install requests "mcp[cli]" openai

Docker Installation

# Using pre-built image
docker run -it --network host ghcr.io/infinitimeless/lmstudio-mcp:latest

# Or build locally
git clone https://github.com/infinitimeless/LMStudio-MCP.git
cd LMStudio-MCP
docker build -t lmstudio-mcp .
docker run -it --network host lmstudio-mcp

Docker Compose

git clone https://github.com/infinitimeless/LMStudio-MCP.git
cd LMStudio-MCP
docker-compose up -d

MCP Configuration

Setup Options

Using GitHub Directly (Simplest)

{
  "lmstudio-mcp": {
    "command": "uvx",
    "args": [
      "https://github.com/infinitimeless/LMStudio-MCP"
    ]
  }
}

Using Local Installation

{
  "lmstudio-mcp": {
    "command": "/bin/bash",
    "args": [
      "-c",
      "cd /path/to/LMStudio-MCP && source venv/bin/activate && python lmstudio_bridge.py"
    ]
  }
}

Using Docker

{
  "lmstudio-mcp-docker": {
    "command": "docker",
    "args": [
      "run",
      "-i",
      "--rm",
      "--network=host",
      "ghcr.io/infinitimeless/lmstudio-mcp:latest"
    ]
  }
}

Usage Guide

Start LM Studio and ensure it's running on port 1234 (the default)
Load a model in LM Studio
Configure Claude MCP with one of the configurations described above
Connect to the MCP server in Claude when prompted

Available Functions

The bridge provides several functions that Claude can use to interact with your local models:

health_check(): Verify if LM Studio API is accessible
list_models(): Get a list of all available models in LM Studio
get_current_model(): Identify which model is currently loaded
chat_completion(prompt, system_prompt, temperature, max_tokens): Generate text from your local model

Troubleshooting

API Connection Issues

If Claude reports 404 errors when trying to connect to LM Studio:

Ensure LM Studio is running and has a model loaded
Check that LM Studio's server is running on port 1234
Verify your firewall isn't blocking the connection
Try using "127.0.0.1" instead of "localhost" in the API URL if issues persist

Model Compatibility

If certain models don't work correctly:

Some models might not fully support the OpenAI chat completions API format
Try different parameter values (temperature, max_tokens) for problematic models
Consider switching to a more compatible model if problems persist

Known Limitations

Some models (e.g., phi-3.5-mini-instruct_uncensored) may have compatibility issues
The bridge currently uses only the OpenAI-compatible API endpoints of LM Studio
Model responses will be limited by the capabilities of your locally loaded model

How to install this MCP server

For Claude Code

To add this MCP server to Claude Code, run this command in your terminal:

claude mcp add-json "lmstudio-mcp" '{"command":"uvx","args":["https://github.com/infinitimeless/LMStudio-MCP"]}'

See the official Claude Code MCP documentation for more details.

For Cursor

There are two ways to add an MCP server to Cursor. The most common way is to add the server globally in the ~/.cursor/mcp.json file so that it is available in all of your projects.

If you only need the server in a single project, you can add it to the project instead by creating or adding it to the .cursor/mcp.json file.

Adding an MCP server to Cursor globally

To add a global MCP server go to Cursor Settings > Tools & Integrations and click "New MCP Server".

When you click that button the ~/.cursor/mcp.json file will be opened and you can add your server like this:

{
    "mcpServers": {
        "lmstudio-mcp": {
            "command": "uvx",
            "args": [
                "https://github.com/infinitimeless/LMStudio-MCP"
            ]
        }
    }
}

Adding an MCP server to a project

To add an MCP server to a project you can create a new .cursor/mcp.json file or add it to the existing one. This will look exactly the same as the global MCP server example above.

How to use the MCP server

Once the server is installed, you might need to head back to Settings > MCP and click the refresh button.

The Cursor agent will then be able to see the available tools the added MCP server has available and will call them when it needs to.

You can also explicitly ask the agent to use the tool by mentioning the tool name and describing what the function does.

For Claude Desktop

To add this MCP server to Claude Desktop:

1. Find your configuration file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
Linux: ~/.config/Claude/claude_desktop_config.json

2. Add this to your configuration file:

{
    "mcpServers": {
        "lmstudio-mcp": {
            "command": "uvx",
            "args": [
                "https://github.com/infinitimeless/LMStudio-MCP"
            ]
        }
    }
}

3. Restart Claude Desktop for the changes to take effect