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LMStudio-MCP

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".

-
security - not tested
A
license - permissive license
-
quality - not tested

local-only server

The server can only run on the client's local machine because it depends on local resources.

A bridge that allows Claude to communicate with locally running LLM models via LM Studio, enabling users to leverage their private models through Claude's interface.

  1. Overview
    1. Prerequisites
      1. Installation
        1. MCP Configuration
          1. Usage
            1. Available Functions
              1. Known Limitations
                1. Troubleshooting
                  1. API Connection Issues
                  2. Model Compatibility
                2. License
                  1. Acknowledgements

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