MCP Server: Comparing Local and Cloud LLMs with Debate Feature

The MCP server is designed to facilitate the comparison of local and cloud-based language models by allowing queries to multiple providers simultaneously. Created by a user known as nesquikm, this tool supports integration with local models through Ollama, as well as cloud APIs including OpenAI, Gemini, Groq, and Together AI.

Key Details

• Providers Supported: Can be pointed at Ollama, LM Studio, or any OpenAI-compatible endpoint.
• Mix and Match Models: Combine local models and various cloud providers in a single query.
• Comparison Features: Answers are displayed side by side, with options for models to vote on the best approach or engage in structured debates, where a third model judges the responses.
• Usage: Quick start with the command npx mcp-rubber-duck. Compatible with multiple IDEs and platforms like Claude Desktop, Cursor, VS Code, or any MCP client, and also deployable via Docker.
• Setup: The repository is available on GitHub at mcp-rubber-duck and is written in TypeScript under the MIT license. Note that this tool is still in early stages and feedback is appreciated, especially from those using local models as providers.

This tool can be particularly useful for developers interested in understanding how different models approach certain problems, especially when discrepancies arise.