LMStudio-MCP: Seamless AI Collaboration | Enterprise Innovation

LMStudio-MCP

A Model Control Protocol (MCP) server that allows Claude to communicate with locally running LLM models via LM Studio.

Overview

LMStudio-MCP creates a bridge between Claude (with MCP capabilities) and your locally running LM Studio instance. This allows Claude to:

• Check the health of your LM Studio API
• List available models
• Get the currently loaded model
• Generate completions using your local models

This enables you to leverage your own locally running models through Claude's interface, combining Claude's capabilities with your private models.

Prerequisites

• Python 3.7+
• LM Studio installed and running locally with a model loaded
• Claude with MCP access
• Required Python packages (see Installation)

Installation

1. Clone this repository:

   git clone https://github.com/infinitimeless/LMStudio-MCP.git

cd LMStudio-MCP

2. Install the required packages:

   pip install requests "mcp[cli]" openai

MCP Configuration

For Claude to connect to this bridge, you need to configure the MCP settings properly. You can either:

1. Use directly from GitHub :

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

}

2. Use local installation :

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

}

For detailed MCP configuration instructions, see MCP_CONFIGURATION.md.

Usage

1. Start your LM Studio application and ensure it's running on port 1234 (the default)

2. Load a model in LM Studio

3. If running locally (not using uvx), run the LMStudio-MCP server:

   python lmstudio_bridge.py

4. In Claude, connect to the MCP server when prompted by selecting "lmstudio-mcp"

Available Functions

The bridge provides the following functions:

• 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

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

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

For more detailed troubleshooting help, see TROUBLESHOOTING.md.

License

MIT

Acknowledgements

This project was originally developed as "Claude-LMStudio-Bridge_V2" and has been renamed and open-sourced as "LMStudio-MCP".