mcp-second-opinion
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Alternatives to mcp-second-opinion
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Related Servers
- AlicenseBqualityDmaintenanceEnables AI agents to consult with multiple AI models (GPT, Gemini, Grok, etc.) through OpenRouter with intelligent auto-selection, conversation history, and caching. Allows your AI assistant to seek expert opinions from specialized models for different tasks like coding, analysis, or general questions.24 npm1MIT
- FlicenseNot gradedqualityCmaintenanceEnables two local LLMs (Qwen and Llama) to communicate via MCP, allowing one model to consult the other for second opinions or additional reasoning.1-

LLM Council MCPofficial
AlicenseNot gradedqualityDmaintenanceEnables Claude Code to consult external LLMs (GPT, Gemini) through multi-turn sessions for second opinions, parallel consultations, and web-grounded research.MIT- AlicenseAqualityAmaintenanceAn MCP server that seats multiple LLMs as a council, letting your assistant query them in parallel or in sequence, relay answers for cross-critique, and merge conclusions within one conversation.672 PyPI2MIT
- AlicenseNot gradedqualityAmaintenanceLets your AI assistant consult assistants from other vendors under your own subscriptions, track costs, and cross-examine answers across models to surface disagreements and open points.2 npmMIT
- AlicenseBqualityFmaintenanceEnables AI assistants to intelligently select and switch between different AI models (OpenAI, Anthropic, etc.) within the same conversation based on task requirements. Provides a unified interface for accessing multiple AI providers through a single MCP tool.122 npmMIT
TDQS
Scored across 2 tools
The two tools have clear boundaries: ask_other_model queries a single rival LLM, while ask_the_panel convenes all enabled LLMs in parallel. There is no meaningful overlap between the two modes.
Both tool names follow a consistent 'ask_<target>' pattern with distinct nouns. This makes the tool set predictable and easy to understand.
Two tools is on the thin side, but it exactly matches the server's stated purpose: get a single second opinion or a panel opinion. Each tool earns its place with no redundancy.
The core use cases of requesting a single rival model or all enabled models are fully covered. A minor gap is the absence of a way to select a specific subset of models, but that may be configuration-level rather than tool-level.