Rubber Duck

Name: Rubber Duck
Author: nesquikm

by nesquikmversion 1.18.0i★ –iRuns on your computer

Registry nameio.github.nesquikm/rubber-duck

Install

Overview

Description from the maker (original English)

Bridge to multiple LLMs and CLI agents: councils, debates, voting, and more

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Search & AI memory
You need to fill in: OPENAI_API_KEY, GEMINI_API_KEY, GROQ_API_KEY

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: OPENAI_API_KEY, GEMINI_API_KEY, GROQ_API_KEY, DEFAULT_PROVIDER

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "rubber-duck": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-rubber-duck"
      ],
      "env": {
        "OPENAI_API_KEY": "your-value",
        "GEMINI_API_KEY": "your-value",
        "GROQ_API_KEY": "your-value",
        "DEFAULT_PROVIDER": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add rubber-duck --env OPENAI_API_KEY=your-value --env GEMINI_API_KEY=your-value --env GROQ_API_KEY=your-value --env DEFAULT_PROVIDER=your-value -- npx -y mcp-rubber-duck

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "rubber-duck": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-rubber-duck"
      ],
      "env": {
        "OPENAI_API_KEY": "your-value",
        "GEMINI_API_KEY": "your-value",
        "GROQ_API_KEY": "your-value",
        "DEFAULT_PROVIDER": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "rubber-duck": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "mcp-rubber-duck"
      ],
      "env": {
        "OPENAI_API_KEY": "your-value",
        "GEMINI_API_KEY": "your-value",
        "GROQ_API_KEY": "your-value",
        "DEFAULT_PROVIDER": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

OPENAI_API_KEY secret env
OpenAI API key (starts with sk-)
GEMINI_API_KEY secret env
Google Gemini API key
GROQ_API_KEY secret env
Groq API key (starts with gsk_)
DEFAULT_PROVIDER env
Default LLM provider to use

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account nesquikm, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 5679 servers in this category
Published to the registry more recently than 8% of the other 5679 servers in this category
Basic checks equal to or better than 100% of the other 5679 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Rubber Duck safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: OPENAI_API_KEY, GEMINI_API_KEY, GROQ_API_KEY

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.18.0) reached the registry 7 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated yesterday

Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 21 days ago

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Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated 2 months ago

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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!

Why direct provider integration? MCP's sampling primitive -- a server borrowing the *host's* model -- was deprecated in the 2026-07-28 spec RC in favor of servers integrating directly with LLM provider APIs. Rubber Duck has always worked this way (it brings its own ducks), so it's aligned with where the protocol is heading -- no migration required.

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)
Spec-Aligned by Design -- connects directly to provider APIs, the path the MCP 2026-07-28 spec recommends now that server-side sampling is deprecated (SEP-2577)

Supported Providers

HTTP Providers (OpenAI-compatible API)

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

OpenAI
Google Gemini
Anthropic (via OpenAI-compatible endpoints)
Groq (fast inference for open-weight models)
Together AI (broad open-weight model catalog)
Perplexity (online models with web search)
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
`OPENAI_DEFAULT_MODEL`	OpenAI model (default: `gpt-5.4`)
`GEMINI_DEFAULT_MODEL`	Gemini model (default: `gemini-3.8-flash`)
`GROQ_DEFAULT_MODEL`	Groq model (default: `openai/gpt-oss-120b`)
`DEFAULT_PROVIDER`	Default provider key: `openai`, `google`, `groq`, `ollama`, or a custom name
`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](./docs/configuration.md)

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](./docs/tools.md)

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](./docs/prompts.md)

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](./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

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

OpenAI gpt-5.6 / gpt-6 Models Fail With the MCP Bridge

OpenAI's Chat Completions API rejects function tools for the gpt-5.6 and gpt-6 families (400 Function tools with reasoning_effort are not supported ... use /v1/responses). They work for plain calls, but with MCP_BRIDGE_ENABLED=true the ducks attach tools and those requests fail. Use gpt-5.4 (the default) or gpt-5.4-mini until Responses API support lands (#166).

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:

Fork the repository
Create a feature branch
Follow our [conventional co

Only the beginning is shown; read the rest in the repo

Rubber Duck

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

MCP Rubber Duck

Features

Supported Providers

HTTP Providers (OpenAI-compatible API)

CLI Providers (Coding Agents)

Quick Start

Or use npx directly in Claude Desktop config

Installation

Prerequisites

Install from NPM

Install from Source

Configuration

Interactive UIs (MCP Apps)

Compare Ducks

Duck Vote

Duck Debate

Usage Stats

Available Tools

Available Prompts

Development

Documentation

Troubleshooting

Provider Not Working

OpenAI gpt-5.6 / gpt-6 Models Fail With the MCP Bridge

Connection Issues

Rate Limiting

Contributing