"Understanding File Usage" matching MCP servers:

MCP server for the Ghost Inspector API that lets agents inspect and manage end-to-end browser tests, offering read-only tools for inventory, module usage, and stale test analysis, plus opt-in guarded write operations.

Read visual bug reports from Feedbug in your AI coding agent: screenshot, console logs, failed network requests, session replay and the DOM context of the element the tester clicked. Trace the bug to its source file, comment and resolve without leaving the editor.

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.

tailtest-cline is a Cline plugin that automatically generates and runs tests every time the agent edits a source file. https://github.com/avansaber/tailtest-cline

Eyes for AI coding agents: deterministic MCP server that tells the LLM which CSS rule wins, in which file, on which line — and why. Cascade verdicts, blast radius, interaction timelines, pixel-perfect audits.

A local MCP server exposing jev_decide for batched classification, rubric scoring, and yes/no judgments with probabilities and token usage. Configure any compatible typed-decision API with API_KEY, BASE_URL, and MODEL.

Admission-control MCP server for AI coding agents — rejects bad file edits without coaching the LLM.

Enables Cursor AI to query SonarQube for pull request metrics, issues, file issues, and duplication reports directly, without manual data export.

Enables building and running custom LLM benchmarks with multi-judge evaluation, supporting GUI, MCP client, and CLI usage for ranked, auditable results.

Local MCP tool for understanding JSON Schema files while planning tests, summarizing types, required fields, constraints, and generating placeholder paths without copying data.

Enables AI agents to safely read, search, and inspect a local git repository, including PR-style diffs and changed-file summaries. It also supports opt-in allowlisted test runs.

Enables AI coding agents to audit web pages for WCAG accessibility and color-contrast issues, and file dev-ready issues directly into OverlayQA projects.

Enables users to run and inspect local prompt-regression evaluations over six labeled fictional outreach cases, comparing a baseline and candidate prompt and reviewing per-case checks, failures, token usage, and stored run records. Exposes four local stdio tools (list_cases, run_demo, list_runs, get_run) for reviewing evidence before a human release decision, without granting paid live runs, file access, shell commands, or release approval.

A MCP server that enables AI assistants to control Android devices via ADB, supporting device info, screen control, input simulation, app management, shell execution, file transfer, and UI parsing.

Turn any .NET test-automation solution into a queryable map in one SQLite file — features, steps, API clients, page objects, and their dependencies. Zero config, no AI, no network, 100% deterministic.

A proxy MCP server that wraps MCP-for-Unity, correcting transport inaccuracies and restricting tool usage for reliable Unity integration.

Enables querying Codecov coverage data including file, commit, repository, and pull request coverage.

Enables agents and users to validate Kubernetes manifests (YAML/JSON, multi-document) against the API of a chosen Kubernetes version without needing a cluster. It reports removed or deprecated APIs with replacements, unknown or misspelt fields, misconfigurations the API server would reject, Pod Security Standard violations, and common risks, each with file, line, and fix.

Enables AI assistants to access RenderDoc capture data and assist in graphics debugging via a file-based IPC bridge.

A unified MCP server for multi-stand infrastructure testing, enabling REST API calls, PostgreSQL queries, and OpenSearch searches through a single config file.

CodeSafer is an MCP server that scans AI-generated code for 9 categories of hidden security threats — including invisible Unicode, Trojan Source, homoglyphs, and rules file backdoors — using static analysis plus CodeBERT deep learning. Runs locally, free tier available.

Provides tools to test regex patterns for correctness, performance (ReDoS), and memory usage, and suggests safe rewrites. Enables LLMs to iterate on regex generation with verifiable feedback.

Provides comprehensive web analysis and auditing tools including HTML extraction, markdown conversion, screenshots, debugging, and Lighthouse-based performance, accessibility, and SEO audits, with token optimization for reduced usage.

Enables AI coding agents to assemble tamper-evident, locally stored evidence bundles that capture Git state, command results, and file hashes, then verify freshness and export shareable reports.

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

Integrates MantisBT bug tracker into Claude and other MCP clients via the REST API. Read and manage issues, notes, file attachments, tags, relationships, and monitors — with optional offline semantic search across all issues.

Enables MCP clients to check whether AI answer engines such as ChatGPT, Claude and Perplexity can read and cite a given site, reporting robots.txt rules, edge-level bot blocks, llms.txt, structured data, JS-only content and other citation blockers with a score and fixes. It can also draft a starter llms.txt file from a site's homepage.

Enables Claude Code to inspect a Godot 4 project's scenes, scripts, autoloads and input actions, compile GDScript through the real engine to surface errors with file and line, run the game or a scene headlessly, read its debug output, and view screenshots of what it renders. It also creates and edits scenes and nodes, with an optional read-only mode that hides every file-changing tool.

AI-powered code review tool that detects AI-generated code defects invisible to traditional linters — hallucinated packages, deprecated APIs, cross-file contradictions, hidden security anti-patterns, and over-engineering. Works as a standalone CLI, GitHub Action, or MCP server. Supports TypeScript, Python, Java, Go, and Kotlin. Free for individuals, no API key required.

A Model Context Protocol (MCP) server that provides comprehensive documentation and usage examples for the AutoFixture testing library.