MCP.Market

Rubber Duck MCP server

by nesquikm·io.github.nesquikm/rubber-duck·v1.18.0·176 stars
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Bridge to multiple LLMs and CLI agents: councils, debates, voting, and more

B83/100grade B
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Safety scan
B83/100

full report

Adoption
Established

176 stars1.6k downloads/wk

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If you have run it, two minutes of your experience saves the next person an afternoon.

Rubber Duck tools (10)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

  • approve_mcp_request

    Approve or deny a duck's MCP tool request

  • ask_duck
  • chat_with_duck

    Have a conversation with a duck, maintaining context across messages

  • clear_conversations

    Clear all conversation history and start fresh

  • duck_council

    Get responses from all configured ducks (like a panel discussion)

  • duck_judge

    Have one duck evaluate and rank other ducks' responses. Use after duck_council to get a comparative evaluation.

  • get_pending_approvals

    Get list of pending MCP tool approvals from ducks

  • list_ducks

    List all available LLM providers (ducks) and their status

  • list_models

    List available models for LLM providers

  • mcp_status

    Get status of MCP bridge, servers, and pending approvals

Public scan report

scanner v0.1.9 · 2026-09-27 · same rubric, same numbers if you re-run it

no findings
  • Code scan217 source files scanned25/25
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitystatic API keys via environment variables6/15
  • Maintenancelast push 13 days ago15/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10
Overall 83/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How Rubber Duck compares

Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
83/100
higher than 65% of 48,255 servers
Tools
10
the typical server has 7
Tools that change things
0%
typical: 0%. Fewer write tools means less an agent can break
GitHub stars
176
more than 95% of 28,688 servers
Downloads a week
1,641
more than 95% of 12,191 servers with a package

What its tools let an agent do: 9 read · 1 change

Install Rubber Duck in Claude Code, Cursor or VS Code

Runs npx -y mcp-rubber-duck on your machine. Read the scan report first; the gateway never runs local packages.

claude mcp add rubber-duck -- npx -y mcp-rubber-duck
Add to Cursor

What the publisher says

From the Rubber Duck repository's README, as published. We do not edit it. Read it on GitHub

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

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)
  • 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

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

Rubber Duck: common questions

Is Rubber Duck MCP server safe?
Mostly: it is graded B (83/100). Read the Rubber Duck safety report
How do I install Rubber Duck?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does Rubber Duck need an API key?
Yes. The registry entry asks for OPENAI_API_KEY, GEMINI_API_KEY, GROQ_API_KEY.
Is Rubber Duck maintained?
The last commit was 50 days ago (2026-09-15). The latest release is v1.18.0.
How does Rubber Duck compare with other MCP servers?
safety score 83/100 (higher than 65% of 48,255 servers); tools 10 (the typical server has 7); tools that change things 0% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.