여러 LLM을 쿼리하는 다리 역할을 하는 MCP(모델 컨텍스트 프로토콜) 서버입니다 — OpenAI 호환 HTTP API와 CLI 코딩 에이전트 모두를 포함합니다. 고무 오리 디버깅처럼, 다양한 AI '오리’에게 문제를 설명하고 다양한 관점을 얻으세요!

왜 직접 제공자 통합인가요? MCP의 sampling 원시 개념 — 호스트 모델을 차용한 서버는 2026년 7월 28일 사양 RC에서 LLM 제공자 API와 직접 통합하는 서버를 선호하여 폐지되었습니다. 러버덕은 항상 이렇게 작동해 왔습니다(자체 덕을 가져옴) 프로토콜의 방향과 일치하여 마이그레이션이 필요하지 않습니다.

특징

• 범용 OpenAI 호환성 – 모든 OpenAI 호환 API 엔드포인트와 호환
• CLI 에이전트 지원 – CLI 코딩 에이전트(Claude Code, Codex, Gemini CLI, Grok, Aider)를 덕으로 사용하세요
• 다중 오리 – 여러 LLM 제공자를 동시에 구성 및 쿼리
• 대화 관리 – 여러 메시지에 걸친 맥락 유지
• Duck Council – 모든 구성된 LLM으로부터 한 번에 응답을 받으세요
• 합의 투표 – 논리와 신뢰도 점수를 포함한 다중 오리 투표

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.)