ultimate-debate-mcp
Enables adversarial collaboration between Claude and GPT for automated code critique, verification, and multi-round debate to improve output quality.
README
Ultimate Debate MCP Server
A Model Context Protocol (MCP) server that enables Claude + GPT adversarial collaboration. GPT-5.2 automatically critiques, debates, and verifies Claude's work for higher-quality outputs.
Features
gpt_critique- Single-pass adversarial critique of code, plans, or textgpt_verify- Verify that fixes actually resolve identified issuesdebate- Multi-round debate loop between Claude and GPT
Requirements
- Node.js >= 20.0.0
- OpenAI API key with GPT-5.2 access
- Claude Code CLI
Installation
1. Clone and Build
git clone https://github.com/YOUR_USERNAME/ultimate-debate-mcp.git
cd ultimate-debate-mcp
npm install
npm run build
2. Install Globally in Claude Code
# Add the MCP server globally (works in any folder)
claude mcp add ultimate-debate --scope user -- node /path/to/ultimate-debate-mcp/dist/index.js
3. Configure Environment Variables
Edit your ~/.claude.json and find the mcpServers section at the root level. Add your OpenAI API key:
{
"mcpServers": {
"ultimate-debate": {
"type": "stdio",
"command": "node",
"args": ["/path/to/ultimate-debate-mcp/dist/index.js"],
"env": {
"OPENAI_API_KEY": "sk-your-openai-api-key",
"OPENAI_MODEL": "gpt-5.2",
"RATE_LIMIT_RPM": "100",
"RATE_LIMIT_RPH": "1000",
"CACHE_MAX_SIZE": "100",
"CACHE_TTL_MS": "3600000"
}
}
}
}
4. Restart Claude Code
Close and reopen Claude Code. Verify installation:
/mcp
You should see ultimate-debate listed with 3 tools.
Configuration Options
| Variable | Default | Description |
|---|---|---|
OPENAI_API_KEY |
required | Your OpenAI API key |
OPENAI_MODEL |
gpt-5.2 |
Model to use (gpt-5.2, gpt-4o, etc.) |
RATE_LIMIT_RPM |
100 |
Max requests per minute |
RATE_LIMIT_RPH |
1000 |
Max requests per hour |
CACHE_MAX_SIZE |
100 |
Max cached responses |
CACHE_TTL_MS |
3600000 |
Cache TTL (1 hour) |
Auto-Collaboration Setup
To make Claude automatically use GPT review, add these rules to your global ~/.claude/CLAUDE.md:
# Auto-Collaboration Rules
When the `ultimate-debate` MCP server is available, automatically:
1. **Before implementation** (>20 lines): Call `gpt_critique` on the plan
2. **After implementation**: Call `gpt_critique` on the code
3. **After fixing issues**: Call `gpt_verify` to confirm resolution
4. **For architecture decisions**: Call `debate` with 2 rounds
## Decision Criteria
| Change Type | Action |
|-------------|--------|
| New feature | `debate` (2 rounds) |
| Bug fix | `gpt_critique` + `gpt_verify` |
| Refactor | `gpt_critique` |
| Trivial (<10 lines) | Skip review |
## Skip Review
Say "skip review" or "no gpt" to bypass auto-collaboration.
Usage Examples
Manual Critique
Ask Claude to review code:
Critique this authentication code for security issues
Manual Debate
For architecture decisions:
Debate whether we should use Redis or PostgreSQL for session storage
Manual Verify
After fixing issues:
Verify the SQL injection fix is complete
MCP Tools Reference
gpt_critique
Single-pass adversarial critique.
Parameters:
content(required) - The content to critiquecontext(optional) - Additional contextfocus_areas(optional) - Array of:logic,security,performance,edge_cases,assumptions,completeness
Returns: Issues with severity (critical/high/medium/low), category, and suggestions.
gpt_verify
Verify fixes are resolved.
Parameters:
original(required) - Original content before fixrevised(required) - Revised content after fixissues_to_check(required) - Array of issues to verify
Returns: Lists of verified, unresolved, and new issues.
debate
Multi-round debate loop.
Parameters:
goal(required) - The objective to debatecontext(optional) - Additional contextartifacts(optional) - Code, diffs, specs, logsrounds(default: 2) - Number of debate rounds (1-5)confidence_threshold(default: 0.8) - Stop early if confidence reachedbudget(optional) - Token and cost limits
Returns: Critical issues, resolved issues, suggested patches, test recommendations.
Development
npm install # Install dependencies
npm run build # Build for production
npm run dev # Development mode with hot reload
npm run test # Run tests
npm run lint # Run linter
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.