"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.

MCP server that detects and guards against tool poisoning and prompt injection attacks in tool descriptions and schemas. It provides risk scoring, pattern detection, safe rewriting, and audit reports with zero external API cost.

MCP server that helps AI agents analyze medical insurance claims, flag anomalies, score risk, and suggest next actions.

Reduces token costs from MCP tool schemas by analyzing bloat, compressing descriptions, and selecting only relevant tools for AI agents.

Analyzes multi-step AI agent tool chains to compute success probability, identify bottlenecks, and suggest better execution orders, enabling more reliable agents via local pure-math computation.

Enables precise financial analysis of AI agent costs, including token pricing, multi-step run estimates, model comparison, and ROI versus human labor, with deterministic decimal math.

Provides accurate SaaS metrics calculations (LTV, CAC, runway, health score, etc.) with formulas and interpretations for AI agents and founders, ensuring no hallucinated numbers.

Scores AI agent trajectories and detects silent failures, loops, and reliability issues with zero external API cost.

Computes AI agent reliability metrics like success rates, latency statistics, and failure patterns from provided numbers, with zero external API cost.

Calculates ROI, break-even, and cost projections for AI agents and automation projects, providing instant answers without external APIs.