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nesquikm/mcp-rubber-duck

An MCP server that acts as a bridge to query multiple OpenAI-compatible LLMs with MCP tool access. Just like rubber duck debugging, explain your problems to various AI "ducks" who can actually research and get different perspectives!

Unclaimed MIT last commit 6 months ago ai
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Scored 3 hours ago · breakdown

About nesquikm/mcp-rubber-duck

nesquikm/mcp-rubber-duck is an MCP server published by nesquikm in the Developer Tools category: an MCP server that acts as a bridge to query multiple OpenAI-compatible LLMs with MCP tool access. Just like rubber duck debugging, explain your problems to various AI "ducks" who can actually research and get different perspectives!. It has been installed 0 times through Conduid.

The repository has 140 stars and 21 forks, with the last commit 6 months ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues (0) before depending on it in production.

Install

Install
npx mcp-rubber-duck
Claude Code
claude mcp add rubber-duck -- npx -y mcp-rubber-duck
npx
npx -y mcp-rubber-duck

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

Ask AI

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I know everything about nesquikm/mcp-rubber-duck. Ask me about installation, configuration, usage, or troubleshooting.

Security checks

  • ·README presentNot checked yet.
  • ·License declaredNot checked yet.
  • ·Tests presentNot checked yet.
  • ·Dependencies pinnedNot checked yet.
  • ·No dynamic code executionNot checked yet.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

Releases

v1.20.5v1.20.5 · 19 Aug 2026[1.20.5](https://github.com/nesquikm/mcp-rubber-duck/compare/v1.20.4...v1.20.5) (2026-08-19) Bug Fixes update LLM pricing data (2026-08-19)…
v1.20.4v1.20.4 · 14 Aug 2026[1.20.4](https://github.com/nesquikm/mcp-rubber-duck/compare/v1.20.3...v1.20.4) (2026-08-14) Bug Fixes mcp-bridge:** warn instead of silently ignoring a global trusted-tools "*"…
v1.20.3v1.20.3 · 10 Aug 2026[1.20.3](https://github.com/nesquikm/mcp-rubber-duck/compare/v1.20.2...v1.20.3) (2026-08-10) Bug Fixes deps:** clear every override-reachable audit-ci advisory…
v1.20.2v1.20.2 · 27 Jul 2026[1.20.2](https://github.com/nesquikm/mcp-rubber-duck/compare/v1.20.1...v1.20.2) (2026-07-27) Bug Fixes deps:** clear audit-ci CVEs (hono, @hono/node-server, fast-uri, postcss)…
v1.20.1v1.20.1 · 21 Jul 2026[1.20.1](https://github.com/nesquikm/mcp-rubber-duck/compare/v1.20.0...v1.20.1) (2026-07-21) Bug Fixes deps:** clear audit-ci CVEs (tar, brace-expansion, js-yaml, body-parser)…

README

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!

npm version Docker Image MCP Registry

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
  • Vision Input -- Send images alongside prompts to vision-capable models (docs)
  • 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.)
  • Structured Output -- outputSchema on tools returning structured JSON for client-side validation (Cursor, VS Code/Copilot)

Supported Providers

HTTP Providers (OpenAI-compatible API)

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

CLI Providers (Coding Agents)

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

# 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

Prerequisites

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

Install from NPM

npm install -g mcp-rubber-duck

Install from Source

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.

Compare Ducks

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

Duck Vote

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

Duck Debate

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

Usage Stats

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

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

Provider Not Working

  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

Connection Issues

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

Rate Limiting

  • 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

Support


Happy Debugging with your AI Duck Panel!

README mirrored from the source repository 3 hours ago. The original is authoritative.

Questions

About nesquikm/mcp-rubber-duck

How do I install nesquikm/mcp-rubber-duck?

Run npx mcp-rubber-duck, then add the server to your MCP client's configuration. Conduid has recorded 0 installs, so the command is known to work with current clients.

Is nesquikm/mcp-rubber-duck safe to use with an AI agent?

Its trust score is 77 out of 100 (good). It passes 0 of 1 static security checks; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is nesquikm/mcp-rubber-duck still maintained?

Yes — the latest release is v1.20.5 (19 Aug 2026), and the last commit was 6 months ago. The repository has 140 stars and 0 open issues.