"Setting up an MCP server in Kubernetes" matching MCP servers:

Enables AI agents and MCP clients to drive real Chrome, Edge, Brave, and Firefox browsers through native automation protocols. It exposes tools for navigation, page snapshots, form filling, clicks, screenshots, console/network inspection, and tab management.

Enables MCP clients to open websites, capture screenshots at multiple breakpoints, and run automated design audits for issues like overflow, small tap targets, low contrast, missing alt text, tiny text, and clipped content.

Enables AI agents to inspect UI screen recordings as token-efficient image sheets with changed regions boxed, single-frame flicker flagged, and speech aligned to frames. Exposes watch_video and zoom_video tools so agents can pull dense keyframes across any time range or one sharp full-resolution frame, all processed locally.

Enables AI assistants to run, list, and analyze Lupa test suites, returning structured JSON results for debugging.

Lets an assistant read recorded production AI agent runs — steps, model and tool calls with arguments, and outcomes — along with the findings of comparison runs that checked a prompt or model change against those recordings, and verify a signed evidence bundle offline with no account or network. It is strictly read-only: no tool starts a replay or comparison, so nothing can spend money or act without a person deciding.

MCP server for remote debugging of Apps in Toss mini-apps, providing CDP relay and test runner capabilities.

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.

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

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.

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.

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

MCP server for managing test cases, cycles, and results in Zephyr Scale on self-hosted Jira. Enables AI agents to create, search, update, and delete test artifacts through natural language.

Translates a lockfile diff into a human-readable upgrade plan. For every dependency bump (npm or PyPI) returns semver class, breaking changes from GitHub release notes, CVEs fixed in the range, migration guide links, and a clear per-package recommendation. Bulk tool ranks up to 50 package changes in parallel by risk (security > caution > review > likely-safe > safe).

MCP server for verifying AI agent claims vs reality — single-transcript inline grounding-check that flags when an agent's response states facts not in the input context, when its code silently swallows exceptions and substitutes mock data, or when its multi-turn transcript contains contradictions or unverified completion claims. Sub-second, local, free, no API calls.

Run the requests in a Postman collection folder and get structured, assertion-level results back straight from your AI assistant.

An MCP server that manages a pool of test accounts, leasing them out one at a time to prevent concurrent session collisions, with automatic reclamation of expired leases.

Enables developers to diagnose why FSE 2.0 CDA2 documents are rejected by validating locally, explaining schematron/XSD errors, looking up code systems, and generating synthetic sample documents.

Provides an isolated workspace for testing candidate code, runs tests, and returns deterministic pass/fail verdicts. Enables automated grading of software engineering solutions by ensuring reproducible test runs.

An MCP server that grades prompts against a validated rubric, tracks real outcomes, and provides guidance grounded in research on what predicts good results.

Provides a check_links tool that lets AI apps verify up to 200 URLs at once, returning status codes, redirect chains, final URLs, and connection errors.

An MCP server that lets an agent read its own eval results, run suites, explain failures, check drift, and view judge calibration status.

Enables AI coding agents to test and automate Android apps rendering UI in OpenGL/Vulkan/Metal surfaces via screenshot-based vision tools for tapping, swiping, long-pressing, and recording, without accessibility tree dependency.

Lets a coding agent lint a Dockerfile or Kubernetes manifest through the Shipshape API, returning an A–F grade, score, pass/fail status, and every finding with its line, fix, and reference. Catches issues like root in the final stage, unpinned base images, curl | sh, secrets in ENV/ARG, and Pod Security Standards, resources, and probes violations before handing work over.

An MCP server that gives AI agents geometric spatial awareness of web page layouts using Playwright, enabling detection of visual occlusion, layout shifts, and spatial relationships.

Wraps Claude Code's code-review skill so any MCP client can run reviews over a PR, branch, working directory, or last commit, with five parallel reviewer subagents, low-to-max effort levels, and optional fix mode that edits files in place. Also supports follow-up questions on a previous review session and a free environment self-check.

An MCP server that gives AI assistants the ability to check open-source packages for vulnerabilities, enrich findings with real-world exploit intelligence, and statically analyse whether vulnerable code is actually reachable in your project.

Detects tests that pass no matter what the code does, revealing vacuous tests that provide false confidence in coverage.

An MCP server that gives AI assistants the ability to inspect, normalize, diff, and validate agent tool-call traces.

MCP server that lets AI agents rent a real UK phone number and receive SMS/OTP verification codes directly in agentic workflows.

Checks that every computed number in a Markdown document still matches the formula that produced it, and repairs it under an explicit write gate — so an agent's correct formula can't ship with a wrong total. Exposes every VisiMark command as a tool (check, explain, eval, infer, format), the authoring discipline as resources, and the orderings an agent gets wrong unsupplied as prompts. Read-only by