"author:princeruhulofficial" matching MCP servers:

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.

This MCP server provides tools to manage, score, compress, and prune AI agent conversation context, helping keep agents focused and reduce token costs. It is a free, local, pure Python solution for any MCP client.

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.

MCP server that analyzes AI agent execution logs to calculate reliability scores, detect failure patterns, and suggest concrete improvements for making AI agents more reliable.

Logs tool call results, calculates reliability scores, and generates reports for AI agents, helping entrepreneurs measure agent reliability without paid APIs.