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Claude-Lmstudio-Bridge_V2
Un servidor Bridge MCP que permite a Claude comunicarse con modelos LLM localmente en ejecución a través de LM Studio
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Claude-LMStudio-Bridge
A simple Model Control Protocol (MCP) server that allows Claude to communicate with locally running LLM models via LM Studio.
Overview
This bridge enables Claude to send prompts to locally running models in LM Studio and receive their responses. This can be useful for:
- Comparing Claude's responses with other models
- Accessing specialized local models for specific tasks
- Running queries even when you have limited Claude API quota
- Keeping sensitive queries entirely local
Prerequisites
- Python 3.8+
- Anthropic Claude with MCP capability
- LM Studio running locally
- Local LLM model(s) loaded in LM Studio
Installation
-
Clone this repository:
git clone https://github.com/infinitimeless/Claude-LMStudio-Bridge_V2.git cd Claude-LMStudio-Bridge_V2
-
Create a virtual environment:
python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate
-
Install the required packages (choose one method):
Using requirements.txt:
pip install -r requirements.txt
Or directly install dependencies:
pip install requests "mcp[cli]" openai anthropic-mcp
Usage
-
Start LM Studio and load your preferred model.
-
Ensure LM Studio's local server is running (usually on port 1234 by default).
-
Run the bridge server:
python lmstudio_bridge.py
-
In Claude's interface, enable the MCP server and point it to your locally running bridge.
-
You can now use the following MCP tools in your conversation with Claude:
-
health_check
: Check if LM Studio API is accessible -
list_models
: Get a list of available models in LM Studio -
get_current_model
: Check which model is currently loaded -
chat_completion
: Send a prompt to the current model
-
Example
Once connected, you can ask Claude to use the local model:
Claude, please use the LM Studio bridge to ask the local model: "What's your opinion on quantum computing?"
Claude will use the chat_completion
tool to send the query to your local model and display the response.
Configuration
By default, the bridge connects to LM Studio at http://localhost:1234/v1
. If your LM Studio instance is running on a different port, modify the LMSTUDIO_API_BASE
variable in lmstudio_bridge.py
.
Troubleshooting
If you encounter issues with dependencies, try installing them directly:
pip install requests "mcp[cli]" openai anthropic-mcp
For detailed installation instructions and troubleshooting, see the Installation Guide.
License
MIT
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
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Reviews

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