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The mcp-rubber-duck MCP server was last committed 15d ago and has 4 contributors. Issue health: 49% of issues resolved. AgentRank freshness score reflects real-time maintenance activity.

mcp-rubber-duck MCP Server

Name: nesquikm/mcp-rubber-duck
Rating: 4.0 (1 reviews)
Author: nesquikm

nesquikm/mcp-rubber-duck

Score: 74.7 ↓ 23.8% Rank #3168 MCP Server

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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!

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Overview

nesquikm/mcp-rubber-duck is a TypeScript MCP server licensed under MIT. 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!

Ranked #3168 out of 24846 indexed tools.

Ecosystem

TypeScript MIT

Score Breakdown

Stars 15% 178

178 stars → growing community

Freshness 25% 15d ago

Last commit 15d ago → recently updated

Issue Health 25% 49%

27/55 issues closed → many open issues

Contributors 10% 4

4 contributors → small team

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A

PyPI Downloads N/A

Forks 25

Description Detailed

License MIT

Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →

How to Improve

Issue Health high impact

You have 28 open vs 27 closed issues — triaging stale issues improves health

Dependents medium impact

No downstream dependents detected yet — adoption by other projects is the strongest trust signal

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Details

Stars: 178
Forks: 25
Open Issues: 28
Closed Issues: 27
Contributors: 4
Dependents: —
Language: TypeScript
License: MIT
Last Commit: 15d ago

Matched Queries

"mcp server""mcp-server"

From the 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!

<p align="center">
  
</p>

> **Why direct provider integration?** MCP's `sampling` primitive -- a server borrowing the *host's* model -- was deprecated in the [2026-07-28 spec RC](https://github.com/modelcontextprotocol/modelcontextprotocol/pull/2577) 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 provid

Read full README on GitHub →