AI Counsel extends LLM Council concept with MCP, Docker, and multi-provider support
u/KobyStam built The AI Counsel, a free open-source tool that extends Andrej Karpathy's LLM Council concept with a Docker-packaged MCP server, two deliberation modes, multi-provider model support, and integrated web search.
Score breakdown
The tool packages multi-model deliberation, MCP server access, and web-grounded search into a single Docker container, giving MCP-compatible agents a drop-in way to replace single-model responses with structured multi-LLM reasoning across both local and cloud providers.
- 01Two deliberation modes: LLM Council (3-stage pipeline: individual replies, anonymous peer reviews, chairman synthesis) and LLM Advisors (persona-based debate with configurable rounds)
- 02Packaged as a Docker container with a built-in MCP server for full API access
- 03Includes a dedicated skill so MCP-compatible agents can call it directly
u/KobyStam released The AI Counsel, a free and fully open-source tool that takes Andrej Karpathy's LLM Council concept further by packaging it as a Docker container with a built-in MCP server. The tool offers two deliberation modes. The LLM Council mode runs a 3-stage pipeline — individual replies, anonymous peer reviews, and chairman synthesis — designed for factual questions and direct answers. The LLM Advisors mode deploys multiple customizable personas (examples given include The Skeptic, The Strategist, and The Ethicist) that debate a question across configurable rounds before reaching consensus and delivering a structured verdict, making it better suited for decisions, strategy, and tradeoffs.
The post notes that everything in the tool is configurable, including system prompts, model temperatures, and advanced debate parameters for the council modes.
The MCP server enables any MCP-compatible agent to connect to the tool directly via a dedicated skill. Model support spans local Ollama models, free cloud options from OpenCode Zen/Go and NVIDIA NIM, and direct API integrations with OpenAI, Anthropic, OpenCode, Mistral, and DeepSeek. To ground responses in current information, the tool integrates four search engines — DuckDuckGo (free, no API key required), Serper, Brave, and TinyFish (all with free tiers) — and uses Jina AI to fetch full articles for the models to read. The post notes that everything in the tool is configurable, including system prompts, model temperatures, and advanced debate parameters for the council modes.
Key facts
- 01Two deliberation modes: LLM Council (3-stage pipeline: individual replies, anonymous peer reviews, chairman synthesis) and LLM Advisors (persona-based debate with configurable rounds)
- 02Packaged as a Docker container with a built-in MCP server for full API access
- 03Includes a dedicated skill so MCP-compatible agents can call it directly
- 04Supports local Ollama models and free cloud models from OpenCode Zen/Go and NVIDIA NIM
- 05Direct integrations with OpenAI, Anthropic, OpenCode, Mistral, and DeepSeek
- 06Search engine support includes DuckDuckGo (free, no API key), Serper, Brave, and TinyFish; Jina AI used for full article fetching
- 07Free and fully open source, available on GitHub
Topics
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