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Enable local AI agents with debate, memory, trust scoring, and governance.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "boardroom-mcp" yet — see the docs or source repo.
Use boardroom-mcp to design a locally running multi-agent decision workflow with 3 advisor roles, debate rounds, trust scoring rules, and a final arbitration mechanism. Output an implementation-ready process description.
A clear multi-agent governance workflow describing roles, discussion steps, scoring, and final decision rules.
Using boardroom-mcp, plan an institutional memory setup for an AI agent that locally stores past conclusions, preserves decision rationale, and retrieves reusable context for new tasks.
A local memory management plan covering what to store, how to retrieve it, update rules, and reuse patterns.
Use boardroom-mcp to create a trust scoring framework for AI agent outputs, including scoring dimensions, weights, exception handling, and triggers for human review.
An actionable trust scoring framework to judge output reliability and decide when escalation is needed.
Runs structured multi-agent debates to compare viewpoints and reach stronger conclusions.
Give AI agents persistent memory, collaboration rooms, and video generation.
Connect local AI coding agents for routing, debate, and efficient context sharing.
Coordinate multiple AI agents in parallel for debate, review, and synthesis.
Coordinate AI agents through negotiation for more efficient automated workflows.
Modular MCP server for agent memory, local access, and secure remote execution.