"Information or resources about video editing" matching MCP servers:

MCP server for screen recording on macOS, iOS Simulator, and Android, with key-frame extraction via ffmpeg, enabling AI agents to capture UI motion and transient visual states.

Validates structured AI video briefs for subject, motion, camera, visual-detail, and audio-direction signals, then builds a portable preflight manifest. Runs locally over stdio and does not call any generation backend.

Enables comprehensive video quality analysis including metadata extraction, GOP structure analysis, quality metrics comparison (PSNR, SSIM, VMAF), artifact detection, and transcoding effect assessment through FFmpeg-based tools.

Records a browser window while Claude drives it and converts the recording into labelled contact sheets, key frames, and an action-correlated timeline for evidence-based evaluation. macOS 15+ only.

Enables agents to control Warcraft III instances in the background for automated map testing, including launching and attaching, sending mouse and keyboard input, capturing screenshots, managing LAN games, and gathering crash and log diagnostics.

Enables agents to discover, search, compare, and inspect tested MCP tools by problem or keyword, with certification verdicts, scorecard summaries, certified scope, and explicit not-tested details.

Enables recurring website maintenance checks — domain registration, SSL certificates, uptime, technical SEO and accessibility — across a portfolio of client sites, using publicly available information. Results are returned as structured data and can be sorted by urgency into a client-ready report.

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

Enables coding agents to compile supplied files, run optional focused tests, and get static findings across ten programming languages, providing a deterministic feedback loop on the code they are about to return.

Checks .docx and .pptx files after automated editing for lost comments, tracked changes and notes.

Exposes MAID Runner validation tools (validate, snapshot, test) as MCP tools, resources, and prompts for AI agents like Claude Code and Aider, enabling seamless integration with AI development workflows.

Exposes six evidence-oriented tools over stdio so MCP clients can navigate unfamiliar code, ask typed questions about repository evidence, review completed changes, and select existing tests.

Umbra is the trust layer for AI-generated code. It scores any repo 0-100 with file:line evidence (security, slop, Docker-verified build/boot, and claim receipts that catch agents lying about tests), and guards agent file writes mid-stream blocking leaked keys, alg:none JWTs, and git-hook plants before they land. Tools: scan_repo, guard_content, get_score.

Enables LLM agents to programmatically inspect, debug, and test other MCP servers by wrapping the MCP Inspector CLI. Supports listing and calling tools, reading resources, and testing prompts on both local and remote MCP servers.

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.

Render, analyze, and verify audio (WAV or FLAC) through a fully offline, deterministic engine, exposed as MCP tools for AI agents.

Enables LLMs to read existing PageSnap session packs and map locators to Playwright, Selenium, or Cypress without capturing or opening a browser.

Generates realistic, referentially-coherent test data (SQL INSERTs, JSON, or CSV) from your database schema, resolving foreign keys and respecting constraints. Paste CREATE TABLE DDL or a JSON schema and get ready-to-run seed data with valid relationships.

MCP server for axe-core accessibility audits. Enables scanning URLs or HTML for WCAG violations with impact levels and fix guidance.

Generates synthetic time-series test data with configurable trend, seasonality, noise, anomalies, and multiple correlated streams, outputting JSON, CSV, or SQL.

Runs SQL statements in memory against real PostgreSQL 18 and SQLite 3.49 engines after loading your schema and sample rows, returning each statement's own verdict: errors with line, column, and hints, constraint violations, or the resulting rows. It also compares both dialects to expose portability differences, all with no database server, network, or API key.

Enables AI-assisted visual regression testing by capturing baselines, comparing screenshots, and using AI to judge whether visual differences are bugs or acceptable changes.

AI-driven mobile app testing via MCP, enabling AI coding agents to test Android apps without test frameworks or testIDs.

Connects AI assistants to the live Godot 4 editor so they can build scenes, scripts, resources and animations, run the game, simulate input, capture screenshots and playtest scenarios, and diagnose runtime errors. Every edit flows through undoable changesets that can be diffed, approved, checkpointed or discarded.

A high-performance, multi-protocol API mock server with 18 built-in MCP tools for managing HTTP, GraphQL, gRPC, WebSocket, MQTT, SSE, and SOAP mocks, chaos engineering, stateful CRUD resources, and request verification.

Enables coding agents to drive and inspect running Shiny apps (R and Python) by setting inputs, clicking, reading outputs, and getting detailed error information.

Automated Playwright E2E test repair powered by a self-improving, governed MCP server that runs failing tests, collects failure artifacts, reasons about root causes, validates and applies fixes, and re-runs to verify.

Enables running Lighthouse web performance audits via MCP, providing Core Web Vitals, performance scores, and optimization suggestions for single or multiple URLs.

An MCP server that turns Zod schemas into mocks, violations, and contract tests, enabling AI agents to reason about API contracts without manually crafting payloads.

An MCP server that lets AI agents run PHP unit and integration tests inside Docker containers without local PHP or Composer.

Enables AI assistants to access RenderDoc capture data and assist with graphics debugging by retrieving draw calls, shader information, buffers, textures, and pipeline state.

Checks MCP servers by URL, npm package, or official MCP Registry search, reporting availability, response speed, exposed tools, resources, and prompts. It flags changes since prior runs as breaking, warning, or info using saved snapshots.

Enables automated testing and demo video creation using Playwright, with login, session orchestration, narration, and video compilation.

MCP server that integrates with Testmo to let AI assistants read projects, runs, results, and test cases, and create or update runs, results, and cases via natural language.

Peeko is a read-only MCP server that provides Claude with screenshots of iOS Simulators, Android emulators, or physical Android devices.

An MCP server for in-loop design review of web previews. It enables agents to submit a preview URL, receive structured findings with suggested fixes, and recheck after applying changes, while never editing code itself.

Enables validating JSON/JSONC, getting/setting values with jq-like paths, pretty-printing or minifying, validating against Ajv JSON Schema, and diffing local files or inline strings without network calls.

Turns JUnit XML test reports from CI into queryable QA metrics, letting AI assistants answer plain-English questions about failures, flaky tests, regressions pinned to a commit, root-cause clusters, and performance drift. Also generates ready-to-share QA health reports and self-contained HTML dashboards without logging into separate tools.

Rarefaction is a Model Context Protocol (MCP) server that gives a coding agent the call graph and code context for one symbol straight from the project's language server (Language Server Protocol, LSP). Ask about a function, method or type and get, in one call: its signature and doc, its body, who calls it (tests marked), what it calls, who implements it, the tests that reach it and the short list

Enables AI agents and developers to inject controlled browser network faults—such as API failures, latency, blocked resources, dropped connections, corrupted payloads, and transient errors—and assert whether web apps recover or degrade gracefully.