LMStudio-MCP
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A Model Control Protocol (MCP) server that allows Claude to communicate with locally running LLM models via LM Studio.
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)
🚀 Quick Installation
One-Line Install (Recommended)
curl -fsSL https://raw.githubusercontent.com/infinitimeless/LMStudio-MCP/main/install.sh | bash
Manual Installation Methods
1. Local Python Installation
git clone https://github.com/infinitimeless/LMStudio-MCP.git
cd LMStudio-MCP
pip install requests "mcp[cli]" openai
2. 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
3. Docker Compose
git clone https://github.com/infinitimeless/LMStudio-MCP.git
cd LMStudio-MCP
docker-compose up -d
For detailed deployment instructions, see .
MCP Configuration
Quick Setup
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"
]
}
}
For complete MCP configuration instructions, see .
Usage
- 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 above
- Connect to the MCP server in Claude when prompted
Available Functions
The bridge provides the following functions:
health_check(): Verify if LM Studio API is accessiblelist_models(): Get a list of all available models in LM Studioget_current_model(): Identify which model is currently loadedchat_completion(prompt, system_prompt, temperature, max_tokens): Generate text from your local model
Deployment Options
This project supports multiple deployment methods:
| Method | Use Case | Pros | Cons |
|---|---|---|---|
| Local Python | Development, simple setup | Fast, direct control | Requires Python setup |
| Docker | Isolated environments | Clean, portable | Requires Docker |
| Docker Compose | Production deployments | Easy management | More complex setup |
| Kubernetes | Enterprise/scale | Highly scalable | Complex configuration |
| GitHub Direct | Zero setup | No local install needed | Requires internet |
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 detailed troubleshooting help, see .
🐳 Docker & Containerization
This project includes comprehensive Docker support:
- Multi-architecture images (AMD64, ARM64/Apple Silicon)
- Automated builds via GitHub Actions
- Pre-built images available on GitHub Container Registry
- Docker Compose for easy deployment
- Kubernetes manifests for production deployments
See for complete containerization documentation.
Contributing
Contributions are welcome! Please see for guidelines.
License
MIT
Acknowledgements
This project was originally developed as "Claude-LMStudio-Bridge_V2" and has been renamed and open-sourced as "LMStudio-MCP".
🌟 If this project helps you, please consider giving it a star!
