infinitimeless claude lmstudio bridge

An MCP server that bridges Claude with local LLMs running in LM Studio.

This tool allows Claude to interact with your local LLMs running in LM Studio, providing:

• Access to list all available models in LM Studio
• The ability to generate text using your local LLMs
• Support for chat completions through your local models
• A health check tool to verify connectivity with LM Studio

• Claude Desktop with MCP support
• LM Studio installed and running locally with API server enabled
• Python 3.8+ installed

1. Clone the repository

git clone https://github.com/infinitimeless/claude-lmstudio-bridge.git
cd claude-lmstudio-bridge

1. Run the setup script

chmod +x setup.sh
./setup.sh

1. Follow the setup script's instructions to configure Claude Desktop

1. Clone the repository

git clone https://github.com/infinitimeless/claude-lmstudio-bridge.git
cd claude-lmstudio-bridge

1. Run the setup script

setup.bat

1. Follow the setup script's instructions to configure Claude Desktop

If you prefer to set things up manually:

1. Create a virtual environment (optional but recommended)

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

1. Install the required packages

pip install -r requirements.txt

1. Configure Claude Desktop:
   • Open Claude Desktop preferences
   • Navigate to the 'MCP Servers' section
   • Add a new MCP server with the following configuration:
     • Name: lmstudio-bridge
     • Command: /bin/bash (on macOS/Linux) or cmd.exe (on Windows)
     • Arguments:
       • macOS/Linux: /path/to/claude-lmstudio-bridge/run_server.sh
       • Windows: /c C:\path\to\claude-lmstudio-bridge\run_server.bat

After setting up the bridge, you can use the following commands in Claude:

1. Check the connection to LM Studio:

Can you check if my LM Studio server is running?

1. List available models:

List the available models in my local LM Studio

1. Generate text with a local model:

Generate a short poem about spring using my local LLM

1. Send a chat completion:

Ask my local LLM: "What are the main features of transformers in machine learning?"

Use the included debugging tool to check your LM Studio connection:

python debug_lmstudio.py

For more detailed tests:

python debug_lmstudio.py --test-chat --verbose

"Cannot connect to LM Studio API"

• Make sure LM Studio is running
• Verify the API server is enabled in LM Studio (Settings > API Server)
• Check that the port (default: 1234) matches what's in your .env file

"No models are loaded"

• Open LM Studio and load a model
• Verify the model is running successfully

"MCP package not found"

• Try reinstalling: pip install "mcp[cli]" httpx python-dotenv
• Make sure you're using Python 3.8 or later

"Claude can't find the bridge"

• Check Claude Desktop configuration
• Make sure the path to run_server.sh or run_server.bat is correct and absolute
• Verify the server script is executable: chmod +x run_server.sh (on macOS/Linux)

You can customize the bridge behavior by creating a .env file with these settings:

LMSTUDIO_HOST=127.0.0.1
LMSTUDIO_PORT=1234
DEBUG=false

Set DEBUG=true to enable verbose logging for troubleshooting.

MIT