Enables MCP clients to run multi-model deliberation (Fusion) via background jobs, using a panel of models and a judge to synthesize high-quality answers.
An MCP server that queries a panel of LLMs from different providers via OpenRouter and returns their answers side by side, optionally synthesizing them to highlight disagreements.
Enables querying multiple AI models in parallel (Claude, Gemini, O3) and synthesizing their responses using anonymous analysis to reduce bias, providing a comprehensive answer.
An MCP server that enables users to query, compare, and synthesize responses from multiple local and cloud LLMs simultaneously using existing subscriptions. It provides tools for parallel model evaluation, consensus polling with an LLM-as-judge, and response synthesis across different model providers.