Claude-LMStudio Bridge

by infinitimeless

3 stars

371 downloads

Not rated

GitHub

About

Bridges Claude with local LLMs running in LM Studio, enabling direct access to local model capabilities for text generation and chat completions while reducing cloud dependency.

Details

Author: infinitimeless
Repository: infinitimeless/claude-lmstudio-bridge
GitHub stars: 3
Downloads: 371
Categories: Community, Developer Tools, AI, API, Communication, Cloud Service

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below
Plugin Name Claude-LMStudio Bridge

Command (node, npx, python, etc.) /bin/bash
Arguments
- Argument 1 /path/to/claude-lmstudio-bridge/run_server.sh
Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "claude-lmstudio bridge": {
            "command": "/bin/bash",
            "args": [
                "/path/to/claude-lmstudio-bridge/run_server.sh"
            ],
            "env": {},
            "shell": false
        }
    }
}

JSON

{
    "mcpServers": {
        "claude-lmstudio bridge": {
            "command": "cmd",
            "args": [
                "/c",
                "C:\\path\\to\\claude-lmstudio-bridge\\run_server.bat"
            ],
            "env": {},
            "shell": false
        }
    }
}

JSON

{
    "mcpServers": {
        "claude-lmstudio bridge": {
            "command": "/bin/bash",
            "args": [
                "/path/to/claude-lmstudio-bridge/run_server.sh"
            ],
            "env": {},
            "shell": false
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "claude-lmstudio bridge": {
            "command": "/bin/bash",
            "args": [
                "/path/to/claude-lmstudio-bridge/run_server.sh"
            ],
            "env": {},
            "shell": false
        }
    }
}

JSON

{
    "mcpServers": {
        "claude-lmstudio bridge": {
            "command": "cmd",
            "args": [
                "/c",
                "C:\\path\\to\\claude-lmstudio-bridge\\run_server.bat"
            ],
            "env": {},
            "shell": false
        }
    }
}

JSON

{
    "mcpServers": {
        "claude-lmstudio bridge": {
            "command": "/bin/bash",
            "args": [
                "/path/to/claude-lmstudio-bridge/run_server.sh"
            ],
            "env": {},
            "shell": false
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "claude-lmstudio bridge": {
            "command": "/bin/bash",
            "args": [
                "/path/to/claude-lmstudio-bridge/run_server.sh"
            ],
            "env": {},
            "shell": false
        }
    }
}

JSON

{
    "mcpServers": {
        "claude-lmstudio bridge": {
            "command": "cmd",
            "args": [
                "/c",
                "C:\\path\\to\\claude-lmstudio-bridge\\run_server.bat"
            ],
            "env": {},
            "shell": false
        }
    }
}

JSON

{
    "mcpServers": {
        "claude-lmstudio bridge": {
            "command": "/bin/bash",
            "args": [
                "/path/to/claude-lmstudio-bridge/run_server.sh"
            ],
            "env": {},
            "shell": false
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "claude-lmstudio bridge": {
            "command": "/bin/bash",
            "args": [
                "/path/to/claude-lmstudio-bridge/run_server.sh"
            ],
            "env": {},
            "shell": false
        }
    }
}

JSON

{
    "mcpServers": {
        "claude-lmstudio bridge": {
            "command": "cmd",
            "args": [
                "/c",
                "C:\\path\\to\\claude-lmstudio-bridge\\run_server.bat"
            ],
            "env": {},
            "shell": false
        }
    }
}

JSON

{
    "mcpServers": {
        "claude-lmstudio bridge": {
            "command": "/bin/bash",
            "args": [
                "/path/to/claude-lmstudio-bridge/run_server.sh"
            ],
            "env": {},
            "shell": false
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "claude-lmstudio bridge": {
            "command": "/bin/bash",
            "args": [
                "/path/to/claude-lmstudio-bridge/run_server.sh"
            ],
            "env": {},
            "shell": false
        }
    }
}

JSON

{
    "mcpServers": {
        "claude-lmstudio bridge": {
            "command": "cmd",
            "args": [
                "/c",
                "C:\\path\\to\\claude-lmstudio-bridge\\run_server.bat"
            ],
            "env": {},
            "shell": false
        }
    }
}

JSON

{
    "mcpServers": {
        "claude-lmstudio bridge": {
            "command": "/bin/bash",
            "args": [
                "/path/to/claude-lmstudio-bridge/run_server.sh"
            ],
            "env": {},
            "shell": false
        }
    }
}

From the repository

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

2. Install the required packages

pip install -r requirements.txt

3. 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?

2. List available models:

List the available models in my local LM Studio

3. Generate text with a local model:

Generate a short poem about spring using my local LLM

4. Send a chat completion:

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

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.

`Check connection to LM Studio`

Check if the LM Studio server is running.

`List available models`

List the available models in your local LM Studio.

`Generate text with a local model`

Generate a short poem or any text using your local LLM.

`Send a chat completion`

Send a prompt to your local LLM and receive a chat completion response.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "claude-lmstudio bridge": {
            "command": "/bin/bash",
            "args": [
                "/path/to/claude-lmstudio-bridge/run_server.sh"
            ],
            "env": {},
            "shell": false
        }
    }
}

Macos

{
    "command": "/bin/bash",
    "args": [
        "/path/to/claude-lmstudio-bridge/run_server.sh"
    ],
    "env": [],
    "shell": false
}

Windows

{
    "command": "cmd",
    "args": [
        "/c",
        "C:\\path\\to\\claude-lmstudio-bridge\\run_server.bat"
    ],
    "env": [],
    "shell": false
}

Linux

{
    "command": "/bin/bash",
    "args": [
        "/path/to/claude-lmstudio-bridge/run_server.sh"
    ],
    "env": [],
    "shell": false
}

Claude-LMStudio Bridge

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

Overview

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

Prerequisites

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

Quick Start (Recommended)

For macOS/Linux:

1. Clone the repository

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

cd claude-lmstudio-bridge

2. Run the setup script

chmod +x setup.sh

./setup.sh

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

For Windows:

1. Clone the repository

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

cd claude-lmstudio-bridge

2. Run the setup script

setup.bat

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

Manual Setup

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

2. Install the required packages

pip install -r requirements.txt

Usage with Claude

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?

2. List available models:

List the available models in my local LM Studio

3. Generate text with a local model:

Generate a short poem about spring using my local LLM

4. Send a chat completion:

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

Troubleshooting

Diagnosing LM Studio Connection Issues

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

Common Issues

"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)

Advanced Configuration

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.

License

MIT

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About

Details

Jump to

Setting up with Highlight

From the repository

Check connection to LM Studio

List available models

Generate text with a local model

Send a chat completion

Claude Desktop / Cursor

Macos

Windows

Linux

Claude-LMStudio Bridge

Overview

Prerequisites

Quick Start (Recommended)

For macOS/Linux:

For Windows:

Manual Setup

Usage with Claude

Troubleshooting

Diagnosing LM Studio Connection Issues

Common Issues

Advanced Configuration

License

Install

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`Check connection to LM Studio`

`List available models`

`Generate text with a local model`

`Send a chat completion`