tribeunal/mcp-server
by Various
MCP server for Tribeunal — 39 tools and 8 Agent Skills that put humans and AI agents on the same jury
MCP
tribeunal/mcp-server
Added 16 Sept 2026
Overview
An MCP server for Tribeunal that exposes 39 tools and 8 Agent Skills for putting humans and AI agents on the same jury. It is written in TypeScript and implements the Model Context Protocol to let clients coordinate mixed human-AI review and decision workflows.
Best for
Best for
Developers building human-AI collaborative decision or review systems on the MCP protocol.
Use cases
- Build a jury-style review process with both human and AI participants
- Orchestrate multi-step evaluation tasks using the provided Agent Skills
- Integrate Tribeunal capabilities into MCP-compatible clients
How to use
Install
npx skills add tribeunal/mcp-server # the entry skill alone Tools exposed
using-tribeunaldeciding-with-a-juryacting-on-verdictsserving-jury-dutyweighing-evidenceconvening-a-team-juryarbitrating-a-disputewiring-webhooks
Tested with
Claude Desktop, Claude Code, Cursor, Windsurf, Cline, VS Code, ChatGPT
Notes
An MCP server for Tribeunal that exposes 39 tools and 8 Agent Skills for putting humans and AI agents on the same jury. It is written in TypeScript and implements the Model Context Protocol to let clients coordinate mixed human-AI review and decision workflows.
1 stars on GitHub. Last updated 2026-09-15. Licensed MIT.
Use cases
- Build a jury-style review process with both human and AI participants
- Orchestrate multi-step evaluation tasks using the provided Agent Skills
- Integrate Tribeunal capabilities into MCP-compatible clients
Pros
- Large tool surface with 39 tools for varied workflow steps
- Includes 8 Agent Skills for higher-level task composition
- TypeScript codebase for type safety and easy contribution
Cons
- Very early stage with only 1 star on GitHub
- Limited community adoption and proven production usage
- Requires an MCP-compatible client to be useful
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Large tool surface with 39 tools for varied workflow steps
- Includes 8 Agent Skills for higher-level task composition
- TypeScript codebase for type safety and easy contribution
Cons
- Very early stage with only 1 star on GitHub
- Limited community adoption and proven production usage
- Requires an MCP-compatible client to be useful
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