"Facebook Live" matching MCP servers:

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

Visual CVE audit dashboard for npm, Python, Go, and Rust projects. Scans your project manifests (package-lock.json, requirements.txt, go.sum, Cargo.lock) against OSV.dev live data, opens a browser dashboard for human review, then applies fixes only after explicit confirmation. Supports multi-service monorepos in one command.

Enables agents to measure a live page or Figma frame against a reference design, reporting exact numerical deviations in layout, spacing, typography, colors, states, and animations before any baseline exists.

MCP server for Seedfast, which fills PostgreSQL databases with realistic, relationally valid test data generated from live schema, providing tools for planning, running, and inspecting seeding operations.

Enables AI agents to score live URLs against a deterministic design contract, validate DTCG tokens and Lottie animations, audit accessibility, and retrieve design-system contracts, catalogs, and review rubrics.

Connects AI agents to Minecraft servers via RCON to execute commands, monitor logs, and perform read-only SQLite database queries. It is specifically designed to facilitate AI-assisted plugin development, live debugging, and automated testing workflows.

Enables passive security scanning of HAR files from QA test automation to detect missing security headers, insecure cookies, CORS misconfigurations, and leaked secrets, without making any live requests.

Enables AI coding agents to diagnose and repair Python Selenium UI automation using real evidence from live DOM and test runs, with enforced safety boundaries and verifiable fixes.

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 over the live protocol. It connects to any MCP target (stdio or HTTP), lints every tool's schema for agent-usability, then actually calls the tools with deliberately broken inputs to see how the server handles them, and returns a 0–100 conformance score with a per-dimension breakdown rendered as Markdown.

Scans live web pages and single-page apps across multiple viewports to detect WCAG 2.1 AA accessibility violations and returns concrete, browser-verified fixes grounded in WCAG success criteria and techniques.

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.

Probes your live API and classifies why each endpoint failed (root cause, evidence, and a calibrated confidence level), exposed over MCP so your AI assistant debugs from evidence instead of guessing. Works with FastAPI, Express, Next.js, tRPC, and GraphQL.

Enables LLMs to automatically diagnose coding errors through codebase search, test execution, and live debugger integration (DAP/V8 CDP). Provides a secure, policy-gated environment for investigating failures while preventing destructive operations.

Connects Claude to a live Chrome browser's accessibility tree to generate stable, framework-agnostic test selectors and perform accessibility audits. It enables users to read element roles and states exactly as a screen reader would to help write, debug, and migrate test suites using natural language.

Visual feedback as agent work packets: stakeholders pin on your live app and your AI coding agent reads each pin (selector, screenshot, DOM, thread, acceptance criteria) via MCP and ships the fix.

An MCP server that gives Claude direct control of a real browser via Playwright, enabling AI-driven web testing, autonomous test execution, and live failure analysis through natural language.

Enables AI agents to run, debug, and inspect Playwright end-to-end tests, returning structured pass/fail stats, failure diagnostics with actionable fix hints, live DOM inspection, selector validation, visual diffs, and flakiness verdicts instead of raw test output.

Enables AI agents to capture screenshots, scrape structured page content, and run automated visual checks on live websites via a headless Chromium browser.

Enables AI assistants to write and debug integration tests by providing live access to DOM structure and executing code directly in test environments.