MCP Rubber Duck

An MCP (Model Context Protocol) server that acts as a bridge to query multiple LLMs -- both OpenAI-compatible HTTP APIs and CLI coding agents. Just like rubber duck debugging, explain your problems to various AI "ducks" and get different perspectives!


Features

- Universal OpenAI Compatibility -- Works with any OpenAI-compatible API endpoint
- CLI Agent Support -- Use CLI coding agents (Claude Code, Codex, Gemini CLI, Grok, Aider) as ducks
- Multiple Ducks -- Configure and query multiple LLM providers simultaneously
- Conversation Management -- Maintain context across multiple messages
- Duck Council -- Get responses from all your configured LLMs at once
- Consensus Voting -- Multi-duck voting with reasoning and confidence scores
- LLM-as-Judge -- Have ducks evaluate and rank each other's responses
- Iterative Refinement -- Two ducks collaboratively improve responses
- Structured Debates -- Oxford, Socratic, and adversarial debate formats
- MCP Prompts -- 8 reusable prompt templates for multi-LLM workflows
- Automatic Failover -- Falls back to other providers if primary fails
- Health Monitoring -- Real-time health checks for all providers
- Usage Tracking -- Track requests, tokens, and estimated costs per provider
- MCP Bridge -- Connect ducks to other MCP servers for extended functionality (docs)
- Guardrails -- Pluggable safety layer with rate limiting, token limits, pattern blocking, and PII redaction (docs)
- Granular Security -- Per-server approval controls with session-based approvals
- Interactive UIs -- Rich HTML panels for compare, vote, debate, and usage tools (via MCP Apps)
- Tool Annotations -- MCP-compliant hints for tool behavior (read-only, destructive, etc.)

Supported Providers

$3

Any provider with an OpenAI-compatible API endpoint, including:

- OpenAI (GPT-5.1, o3, o4-mini)
- Google Gemini (Gemini 3, Gemini 2.5 Pro/Flash)
- Anthropic (via OpenAI-compatible endpoints)
- Groq (Llama 4, Llama 3.3)
- Together AI (Llama 4, Qwen, and more)
- Perplexity (Online models with web search)
- Anyscale, Azure OpenAI, Ollama, LM Studio, Custom

$3

Command-line coding agents that run as local processes:

- Claude Code (claude) -- Codex (codex) -- Gemini CLI (gemini) -- Grok CLI (grok) -- Aider (aider) -- Custom

See CLI Providers for full setup and configuration.

Quick Start

``bash


Install globally

npm install -g mcp-rubber-duck

Or use npx directly in Claude Desktop config

npx mcp-rubber-duck
`

Using Claude Desktop? Jump to Claude Desktop Configuration.
Using Cursor, VS Code, Windsurf, or another tool? See the Setup Guide.

Installation

$3

- Node.js 20 or higher
- npm or yarn
- At least one API key for an HTTP provider, or a CLI coding agent installed locally

$3

`bash
npm install -g mcp-rubber-duck
`

$3

`bash
git clone https://github.com/nesquikm/mcp-rubber-duck.git
cd mcp-rubber-duck
npm install
npm run build
npm start
`

Configuration

Create a .env file or config/config.json. Key environment variables:

| Variable | Description |
|----------|-------------|
| OPENAI_API_KEY | OpenAI API key |
| GEMINI_API_KEY | Google Gemini API key |
| GROQ_API_KEY | Groq API key |
| DEFAULT_PROVIDER | Default provider (e.g., openai) |
| DEFAULT_TEMPERATURE | Default temperature (e.g., 0.7) |
| LOG_LEVEL | debug, info, warn, error |
| MCP_SERVER | Set to true for MCP server mode |
| MCP_BRIDGE_ENABLED | Enable MCP Bridge (ducks access external MCP servers) |
| CUSTOM_{NAME}_* | Custom HTTP providers |
| CLI_{AGENT}_ENABLED | Enable CLI agents (CLAUDE, CODEX, GEMINI, GROK, AIDER) |

Full reference: Configuration docs

Interactive UIs (MCP Apps)

Four tools -- compare_ducks, duck_vote, duck_debate, and get_usage_stats -- can render rich interactive HTML panels inside supported MCP clients via MCP Apps. Once this MCP server is configured in a supporting client, the UIs appear automatically -- no additional setup is required. Clients without MCP Apps support still receive the same plain text output (no functionality is lost). See the MCP Apps repo for an up-to-date list of supported clients.

$3

Compare multiple model responses side-by-side, with latency indicators, token counts, model badges, and error states.





$3

Have multiple ducks vote on options, displayed as a visual vote tally with bar charts, consensus badge, winner card, confidence bars, and collapsible reasoning.





$3

Structured multi-round debate between ducks, shown as a round-by-round view with format badge, participant list, collapsible rounds, and synthesis section.





$3

Usage analytics with summary cards, provider breakdown with expandable rows, token distribution bars, and estimated costs.





Available Tools

| Tool | Description |
|------|-------------|
| ask_duck | Ask a single question to a specific LLM provider |
| chat_with_duck | Conversation with context maintained across messages |
| clear_conversations | Clear all conversation history |
| list_ducks | List configured providers and health status |
| list_models | List available models for providers |
| compare_ducks | Ask the same question to multiple providers simultaneously |
| duck_council | Get responses from all configured ducks |
| get_usage_stats | Usage statistics and estimated costs |
| duck_vote | Multi-duck voting with reasoning and confidence |
| duck_judge | Have one duck evaluate and rank others' responses |
| duck_iterate | Iteratively refine a response between two ducks |
| duck_debate | Structured multi-round debate between ducks |
| mcp_status | MCP Bridge status and connected servers |
| get_pending_approvals | Pending MCP tool approval requests |
| approve_mcp_request | Approve or deny a duck's MCP tool request |

Full reference with input schemas: Tools docs

Available Prompts

| Prompt | Purpose | Required Arguments |
|--------|---------|-------------------|
| perspectives | Multi-angle analysis with assigned lenses | problem, perspectives |
| assumptions | Surface hidden assumptions in plans | plan |
| blindspots | Hunt for overlooked risks and gaps | proposal |
| tradeoffs | Structured option comparison | options, criteria |
| red_team | Security/risk analysis from multiple angles | target |
| reframe | Problem reframing at different levels | problem |
| architecture | Design review across concerns | design, workloads, priorities |
| diverge_converge | Divergent exploration then convergence | challenge |

Full reference with examples: Prompts docs

Development

`bash
npm run dev # Development with watch mode
npm test # Run all tests
npm run lint # ESLint
npm run typecheck # Type check without emit
`

Documentation

| Topic | Link |
|-------|------|
| Setup guide (all tools) | docs/setup.md |
| Full configuration reference | docs/configuration.md |
| Claude Desktop setup | docs/claude-desktop.md |
| All tools with schemas | docs/tools.md |
| Prompt templates | docs/prompts.md |
| CLI coding agents | docs/cli-providers.md |
| MCP Bridge | docs/mcp-bridge.md |
| Guardrails | docs/guardrails.md |
| Docker deployment | docs/docker.md |
| Provider-specific setup | docs/provider-setup.md |
| Usage examples | docs/usage-examples.md |
| Architecture | docs/architecture.md |
| Roadmap | docs/roadmap.md |

Troubleshooting

$3


1. Check API key is correctly set
2. Verify endpoint URL is correct
3. Run health check: list_ducks({ check_health: true })
4. Check logs for detailed error messages

$3

- For local providers (Ollama, LM Studio), ensure they're running
- Check firewall settings for local endpoints
- Verify network connectivity to cloud providers

$3

- Configure failover to alternate providers
- Adjust max_retries and timeout settings
- See Guardrails for rate limiting configuration

Contributing

`
__
<(o )___
( ._> /
---' Quack! Ready to debug!
``

We love contributions! Whether you're fixing bugs, adding features, or teaching our ducks new tricks, we'd love to have you join the flock.

Check out our Contributing Guide to get started.

Quick start for contributors:
1. Fork the repository
2. Create a feature branch
3. Follow our conventional commit guidelines
4. Add tests for new functionality
5. Submit a pull request

License

MIT License - see LICENSE file for details

Acknowledgments

- Inspired by the rubber duck debugging method
- Built on the Model Context Protocol (MCP)
- Uses OpenAI SDK for HTTP provider compatibility
- Supports CLI coding agents (Claude Code, Codex, Gemini CLI, Grok, Aider)

Changelog

See CHANGELOG.md for a detailed history of changes and releases.

Registry & Directory

- NPM Package: npmjs.com/package/mcp-rubber-duck
- Docker Images: ghcr.io/nesquikm/mcp-rubber-duck
- MCP Registry: Official MCP server io.github.nesquikm/rubber-duck`
- Glama Directory: glama.ai/mcp/servers/@nesquikm/mcp-rubber-duck
- Awesome MCP Servers: Listed in the community directory

Support

- Report issues: https://github.com/nesquikm/mcp-rubber-duck/issues
- Documentation: https://github.com/nesquikm/mcp-rubber-duck/wiki
- Discussions: https://github.com/nesquikm/mcp-rubber-duck/discussions

---

Happy Debugging with your AI Duck Panel!