"author:princeruhulofficial" matching MCP servers:

Audits MCP tool descriptions for quality and reliability, scoring them 0-100, detecting smells, and providing rewritten versions for better agent accuracy.

Resolves messy company, customer, and vendor names across CRM, ERP, and ITSM systems to canonical records using fuzzy matching, preventing AI agents from updating or creating wrong or duplicate records.

MCP server that scores tool descriptions, estimates token costs, simulates agent tool selection, and generates reliability reports to help AI agents choose the right tools and reduce wasted tokens.

MCP server for measuring, tracking, scoring, and improving AI agent reliability with tools for recording interactions, scoring reliability, analyzing failures, recommending improvements, generating audit reports, and checking MCP health.

MCP server that computes trust scores, permission decisions, and silent-failure risk for AI agents with tools for reliability scoring, silent failure detection, permission evaluation, and audit report generation.