llm-council: LLM Council is a multi-LLM deliberation system that enables multiple large language models to collaboratively answer questions through a three-stage process: independent responses, anonymous peer review, and chairman synthesis. It supports various LLM gateways and can be deployed as a Python library, MCP server, or HTTP API. Designed for high-quality, balanced answers with features like rubric scoring, bias auditing, and offline mode.; MCP-Chinese-Getting-Started-Guide: This guide provides a rapid introduction to the Model Context Protocol (MCP), an open-source protocol standardizing LLM interactions with external data and tools. It demonstrates building and debugging MCP servers, developing MCP clients for LLMs like DeepSeek, and integrating with Claude Desktop.
Complex reasoning and decision-making requiring diverse AI perspectives
Enhancing LLMs with real-time web search capabilities