"A tool for reading PDF files" 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.

Generates test files locally (images, PDFs, CSVs, corrupted files, etc.) from natural language prompts, with configurable sizes and safety limits.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Local Markdown-to-PDF MCP server with four tools to list themes, render a document, validate an existing PDF, and create a document from a template. Requires Python, Pango/GLib, and fonts; its 0–100 report is heuristic, not print or accessibility certification.

Enables verification of deployment-scoped model-visible DSH tool surface conformance by checking recorded tool identities and schemas against approved locks, reporting only drift categories and hashes.

Protects AI agents from bad tool outputs, schema mismatches, and tool poisoning by validating, sanitizing, and scoring reliability of tool responses.

An MCP Server that provides access to Google's Cloud Tool Results API, enabling applications to programmatically interact with test results from Firebase Test Lab and mobile app testing through natural language.

A lightweight multi-provider MCP testing fixture with two providers (eva_air and uk_railway), each exposing 5 tools using in-memory fake data, designed for verifying MCP client tool discovery, tool calls, and multi-provider routing.

This MCP server verifies that an agent’s claimed tool output matches the actual response returned by a tool to prevent invented or distorted results. It flags mismatches, omissions, and invented fields to ensure downstream logic only processes verified tool data.

Feedback ingestion for AI agents. Record your screen and talk; your agent does the rest — files the bugs, writes the spec, builds the backlog.

MCP server exposing statistical regression testing for LLM agents as a "run" tool: p-value, effect size, and confidence interval on whether agent behavior actually changed.

Enables read-only analysis of FST waveform files, including signal value queries, timing measurements, event search, latency analysis, and PNG plot generation using human-readable time addressing.

A Model Context Protocol (MCP) server for debugging and operating Rust Tauri applications over WebSocket.

MCP server exposing a "run" tool that benchmarks agent-memory backends and returns a reproducible JSON report.

Free church website audit: an MCP server that checks a church homepage for mobile, speed, SEO and first-time-visitor basics.

Free MCP tools for context engineering audits of AI agents, offering on-demand analysis of system prompts, tool definitions, and context packing.

A deterministic preflight checker for outbound SMS/iMessage that catches silent filtering, segment blowups, and dropped iMessage features before sending.

Measures what MCP servers cost in context tokens: probes a URL or a local command now, measures a whole config file, and looks up the daily results for every server in the official MCP registry on mcpcost.ulehla.dev.

A Model Context Protocol (MCP) server for interacting with SonarQube code quality platform.

Provides an in-memory notebook interface with tools to create, retrieve, list, update, and delete notes, designed to test agent behavior through realistic MCP tool interactions.

Enables AI assistants to inspect generated .docx and .pdf files before delivery, extracting structural, typographic, spacing, and language facts so formatting errors can be caught automatically.

A local MCP server that routes QA reviews through deterministic profiles and risk-based escalation while keeping source evidence and final decisions with the host.

Renders HTML in a headless browser and detects layout defects numerically, such as text overlaps, placeholder leftovers, and element overflow, without requiring baseline images.

Lets AI agents ask which tests a Playwright or Vitest project contains, which are skipped and why, by reading the test source files statically. Nothing is executed, written, or sent over the network, and answers come back as paged JSON with summaries, filters, and scan diagnostics.

Enables AI agents to drive the 1C:Enterprise test client directly, opening forms, reading and modifying data, working with tables, and recording or replaying action scenarios. Connects to local or remote test clients over their network protocol without a testing manager.

Enables a coding agent to answer "is this iOS release ready?" by running read-only App Store Connect checks: build processing, App Review state, a 13-point submission preflight, release-notes policy linting, and App Store Server Notification reconciliation. The lone write capability is a dry-run-first, seven-gate submission tool that always requires explicit confirmation.

A universal MCP server that dynamically generates and simulates actions for any query, maintaining state between sessions.

MCP server providing three QA tools: parse JUnit XML reports, detect flaky tests across multiple runs, and evaluate quality gates with pass/fail decisions.

AI-powered QA testing platform — catches JS errors, accessibility failures, visual regressions, API loops, security issues, and more via Chrome DevTools MCP

Scan any project or website for privacy compliance issues directly in your AI coding tool. Detects tracking tech, cookies, and third-party data collection. Works in Claude Code, Cursor, and Windsurf.