Toolrank

ToolRank MCP Server Score and optimize MCP tool definitions for AI agent discovery.

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What it can do

  • Toolrank Score: Analyzes MCP tool definitions and returns a ToolRank Score (0-100) measuring agent-readiness. Evaluates four dimensions: Findability (25%), Clarity (35%), Precision (25%), and Efficien
  • Toolrank Suggest: Generates specific improvement suggestions for MCP tool definitions to increase their ToolRank Score. Use this when you have a low score and want actionable fix recommendations. Retu

What data it sees

Do you need an account

No: the server works without sign-in

ToolRank MCP Server

Score and optimize MCP tool definitions for AI agent discovery. The first ATO (Agent Tool Optimization) platform.

Tools

toolrank_score

Analyzes MCP tool definitions and returns a ToolRank Score (0-100) measuring agent-readiness. Evaluates four dimensions: Findability (25%), Clarity (35%), Precision (25%), and Efficiency (15%). Returns per-tool scores, maturity level, specific issues found, and fix suggestions ranked by impact.

toolrank_suggest

Generates specific improvement suggestions for MCP tool definitions. Returns rewritten descriptions, improved schemas, and estimated score improvements.

Install

npx @toolrank/mcp-server

Links

Server tool list (2)

Raw names from tools/list. Only developers need these.

toolrank_scoreAnalyzes MCP tool definitions and returns a ToolRank Score (0-100) measuring agent-readiness. Evaluates four dimensions: Findability (25%), Clarity (35%), Precision (25%), and Efficiency (15%). Use this when you want to check or improve the quality of your MCP tool definitions. Returns per-tool scores, maturity level, specific issues found, and fix suggestions ranked by impact.
toolrank_suggestGenerates specific improvement suggestions for MCP tool definitions to increase their ToolRank Score. Use this when you have a low score and want actionable fix recommendations. Returns rewritten description, improved schema, and estimated score improvement for each suggestion.