Content
# Cognition Wheel MCP Server
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.
## Quick Start
### Option 1: Use with npx (Recommended)
```bash
# Run directly with npx (no installation needed)
npx mcp-cognition-wheel
# Or install globally
npm install -g mcp-cognition-wheel
mcp-cognition-wheel
```
### Option 2: Build from source
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`
## How It Works
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
## Features
- **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
## Installation
### Option 1: Use with npx (Recommended)
```bash
# Run directly with npx (no installation needed)
npx mcp-cognition-wheel
# Or install globally
npm install -g mcp-cognition-wheel
mcp-cognition-wheel
```
### Option 2: Build from source
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`
## Usage
This is an MCP server designed to be used with MCP-compatible clients like Claude Desktop or other MCP tools.
### Required Environment Variables
- `ANTHROPIC_API_KEY`: Your Anthropic API key
- `GOOGLE_GENERATIVE_AI_API_KEY`: Your Google AI API key
- `OPENAI_API_KEY`: Your OpenAI API key
### Using with Cursor
Based on the guide from [this dev.to article](https://dev.to/andyrewlee/use-your-own-mcp-on-cursor-in-5-minutes-1ag4), here's how to integrate with Cursor:
#### Option 1: Using npx (Recommended)
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:
```json
{
"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"
}
}
}
```
#### Option 2: Using local build
1. **Build the project** (if not already done):
```bash
pnpm run build
```
2. **Configure the server**:
- **Name**: `cognition-wheel`
- **Command**: `node`
- **Args**: `["/absolute/path/to/your/cognition-wheel/dist/app.js"]`
Example configuration:
```json
{
"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
### Tool Usage
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
## Development
- `pnpm run dev`: Watch mode for development
- `pnpm run build`: Build the TypeScript code
- `pnpm run start`: Run the server directly with tsx
## Docker
Build and run with Docker:
```bash
# Build the image
docker build -t cognition-wheel .
# Run with environment variables
docker run --rm \
-e ANTHROPIC_API_KEY=your_key \
-e GOOGLE_GENERATIVE_AI_API_KEY=your_key \
-e OPENAI_API_KEY=your_key \
cognition-wheel
```
## License
MIT
