Show HN: Cognition-wheel – parallel LLM fusion with bias masking and judging

A Model Context Protocol (MCP) server that implements a "wisdom of crowds" approach to AI reasoning by consulting multiple state-of-the-art language models in parallel and synthesizing their responses.

1. Clone the repository
2. Install dependencies: pnpm install
3. Copy .env.example to .env and add your API keys
4. Build the project: pnpm run build

The Cognition Wheel follows a three-phase process:

1. Parallel Consultation: Simultaneously queries three different AI models:

   • Claude-4-Opus (Anthropic)
   • Gemini-2.5-Pro (Google)
   • O3 (OpenAI)

2. Anonymous Analysis: Uses code names (Alpha, Beta, Gamma) to eliminate bias during the synthesis phase

3. Smart Synthesis: Randomly selects one of the models to act as a synthesizer, which analyzes all responses and produces a final, comprehensive answer

• Parallel Processing: All models are queried simultaneously for faster results
• Bias Reduction: Anonymous code names prevent synthesizer bias toward specific models
• Internet Search: Optional web search capabilities for all models
• Detailed Logging: Comprehensive debug logs for transparency and troubleshooting
• Robust Error Handling: Graceful degradation when individual models fail

1. Clone the repository
2. Install dependencies: pnpm install
3. Copy .env.example to .env and add your API keys
4. Build the project: pnpm run build

This is an MCP server designed to be used with MCP-compatible clients like Claude Desktop or other MCP tools.

• ANTHROPIC_API_KEY: Your Anthropic API key
• GOOGLE_GENERATIVE_AI_API_KEY: Your Google AI API key
• OPENAI_API_KEY: Your OpenAI API key

Based on the guide from this dev.to article, here's how to integrate with Cursor:

1. Open Cursor Settings:

   • Go to Settings → MCP
   • Click "Add new MCP server"

2. Configure the server:

   • Name: cognition-wheel
   • Command: npx
   • Args: ["-y", "mcp-cognition-wheel"]

   Example configuration:

   { "cognition-wheel": { "command": "npx", "args": ["-y", "mcp-cognition-wheel"], "env": { "ANTHROPIC_API_KEY": "your_anthropic_key", "GOOGLE_GENERATIVE_AI_API_KEY": "your_google_key", "OPENAI_API_KEY": "your_openai_key" } } }

1. Build the project (if not already done):

2. Configure the server:

   • Name: cognition-wheel
   • Command: node
   • Args: ["/absolute/path/to/your/cognition-wheel/dist/app.js"]

   Example configuration:

   { "cognition-wheel": { "command": "node", "args": [ "/Users/yourname/path/to/cognition-wheel/dist/app.js" ], "env": { "ANTHROPIC_API_KEY": "your_anthropic_key", "GOOGLE_GENERATIVE_AI_API_KEY": "your_google_key", "OPENAI_API_KEY": "your_openai_key" } } }

3. Test the integration:

   • Enter Agent mode in Cursor
   • Ask a complex question that would benefit from multiple AI perspectives
   • The cognition_wheel tool should be automatically triggered

The server provides a single tool called cognition_wheel with the following parameters:

• context: Background information and context for the problem
• question: The specific question you want answered
• enable_internet_search: Boolean flag to enable web search capabilities

• pnpm run dev: Watch mode for development
• pnpm run build: Build the TypeScript code
• pnpm run start: Run the server directly with tsx

Build and run with Docker:

MIT