"Checking Supabase migrations in GitHub Actions" 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 GitHub Copilot Agent Mode to act as a QA assistant by providing MCP tools to query and modify Bugzilla bugs, Jira issues, and Confluence pages through natural language.

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.

Enables natural-language testing of MCP servers—covering tools, resources, prompts, contracts, and transports—without writing test code, with deterministic validation and CI integration.

Runs as an MCP server that lets an agent grade other MCP servers for agent usability, explain grading rules, and list available rules. It enables automated assessment of tool descriptions, schemas, naming, token cost, consistency, and optional live evaluation.

An MCP server for n8n that gives AI agents tools for generating workflows, linting, diagnosing failed executions, and driving live n8n instances.

A stdio MCP server that audits other MCP servers by linting their tool schemas and calling tools with malformed inputs to produce a 0–100 conformance score and Markdown report.

Enables AI agents and developers to independently verify code and documentation claims against the repository, producing evidence-backed audit reports and pull-request checks.

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

Enables agents to grade other MCP servers for LLM usability, covering descriptions, schema design, naming, token cost, and consistency, while also explaining grading rules.

Lets users inspect and verify content-addressed schema migration evidence offline, checking idempotence, reversible rollback, required invariants, and explicit lossy-field disclosure without executing migrations or accessing data.

Enables coding agents to verify whether a GitHub pull request is genuinely ready by checking draft state, conflicts, check results on the head commit, review requirements, merge queue status, and expected commit, returning a verdict with reasons and owners pinned to a commit and timestamp. It reports merged or closed PRs without judging them and never authorizes a merge.

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.

Enables AI coding tools to run CheckMyLaunch scans on GitHub repos or live URLs and retrieve findings and repair prompts directly within the chat.

Local-first bug reports for coding agents: annotated screenshots, recordings and notes stored on your machine, served over MCP with the images included. Sync reports to GitHub issues when you choose.

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

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

Provides instant GDScript syntax validation and diagnostics by bridging Godot's native Language Server Protocol to MCP clients. Enables real-time syntax checking in AI assistants without requiring custom plugins or context switching to the Godot editor.

MCP bridge that lets any MCP client drive the Alethia runtime for agent-native E2E testing. It provides a per-step policy gate that blocks destructive actions with a cryptographic audit trail.

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).

Enables AI assistants to summarize Playwright test runs, identify flaky tests, heuristically triage failures, generate Playwright test stubs, and retrieve recent GitHub CI status through MCP tool calls.

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

AI 規格大師 — MCP server bridging specs (Linear / JIRA / GitHub Issues / Notion / Markdown / Figma) to tests, with bidirectional traceability and a spec-quality coach. Sibling to mk-qa-master.

Enables verification that a synthesized passage preserves the human-ness of source passages by checking exact copies, logged deletions/reorderings, and flagged unverified transformations.

Diffgate MCP server acts as a code review engine, enabling AI coding agents to analyze and validate code diffs before application. It enhances AI workflows by providing self-checking capabilities to optimise and secure code changes.

Automates the evaluation of GitHub hackathon submissions by providing tools to collect issue data, apply scoring rubrics, and generate ranking reports. It enables a multi-agent system to manage scoring consistency, statistical outlier detection, and feedback generation through the GitHub CLI.

Enables agents to verify that a deploy actually worked by checking pages, links, and comparing environments, catching blank 200 responses, broken links, stray noindex, and staging that never updated.

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.

MCP server that lets Claude diagnose failed GitHub Actions runs by fetching and parsing CI logs into structured failure signals, enabling natural-language questions like 'Why did the last run fail?'.

Controls any built Tauri app's UI via WebDriver, enabling mouse/keyboard actions, DOM inspection, and screenshots.

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

Diagnoses HLS and DASH streams by reading manifests over HTTP, checking rendition ladders, segment timing, live windows, and DRM, and reports issues with evidence—no ffmpeg required.

MCP server that helps AI agents create UIs that don't look AI-generated by auditing components, refining copy, suggesting themes, and checking accessibility/contrast.

Scores npm packages, PyPI packages and GitHub repositories 0-100 with an A-F grade and plain-language risks. Scans package.json, requirements.txt and lock files; no API key needed.

Enables AI agents to simulate network failures and test application resilience in Playwright browser sessions.

Enables AI agents to verify that every number, money amount, percentage, count, date and time in an AI-written Japanese summary or meeting minutes actually appears in the source text, normalizing kanji numerals, 万/億, full-width digits, Japanese era years, 午前/午後 times and 割/分 rates before comparison. Exposes a read-only check tool that reports each fact as supported, approximate, mismatched or unsupported, plus an extraction tool that lists the quantities in a text.

Enables Codex to inspect, test, and control Android emulators through adb with strict typed tools, returning screenshots as native MCP images and keeping physical devices and Gradle execution behind explicit opt-in policies.