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.
📖 Read the full source: r/LocalLLaMA
👀 See Also
Skills Creator Tool for OpenClaw Helps Developers Package Workflows
A developer created a skill called skills-creator that guides users through creating quality skills for OpenClaw, addressing common pitfalls like vague descriptions and documentation-like instructions. It's available on ClawHub and provides a design-driven approach with description formulas, checklists, and complexity tiers.
Token Reducer: A Claude Code Plugin for Intelligent Context Compression
Token Reducer is a Claude Code plugin that processes repository context locally to reduce token usage by 90-98% using AST-based chunking, hybrid retrieval, and TextRank compression. It's MIT licensed and available via the plugin marketplace.
Local Qwen Models Achieve Browser Automation with Stepwise Planning and Compact DOM
A developer found small local LLMs like Qwen 8B and 4B succeed at browser automation using stepwise planning instead of upfront multi-step plans, combined with a compact semantic DOM representation that reduces token usage from 50-100K+ to ~15K for full flows.
AgentPeek: Open-source dashboard for monitoring Claude Code agent teams
AgentPeek is a local dashboard that hooks into Claude Code to provide visibility into agent teams, showing orchestration hierarchies, execution traces, token costs, and file operations. Installation requires cloning the GitHub repo and running pipx install.