"How to Capture Screenshots from YouTube Videos" matching MCP servers:

A runtime-free MCP server that converts source code into AST🌲, regardless of language.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

Enables automated migration of Vue projects to React with intelligent analysis, task management, and learning from user modifications.

Enables Claude to use Google Gemini as a secondary AI through MCP for large-scale codebase analysis and complex reasoning tasks. Supports both Gemini Flash and Pro models with specialized functions for general queries and comprehensive code analysis.

Enables AI coding agents to extract Figma design data and convert it into Flutter widgets and screens. Supports theme setup, component analysis, asset exports, and provides Flutter implementation guidance from Figma designs.

Enables AI assistants to analyze project folders for dependencies and frameworks and fetch current documentation or datasheets from the web.

Enables migration of test automation projects from WebDriverIO to Playwright using AST-based transformations. Provides tools for analyzing tests, converting syntax, refactoring to Page Object Model, and generating migration reports.

Converts vector PDF circuit schematics into evidence-preserving SchematicIR JSON with tools to inspect, convert, and validate schematic PDFs.

Enables MCP clients such as Claude Desktop or Cursor to inspect a coffee-shop sales database schema, validate SQL, and run guarded read-only queries. It supports natural-language questions by exposing tools for schema description, SQL checking, and safe query execution.

Translate Python between English and your language, with round-trip verification. Pack-based and reviewed, not model-guessed: translate files both ways, look up how terms render, check identifier names, and report how legible a codebase is in a language, all locally with uvx legesher-mcp.

Enables coding agents to capture and inspect running projects, resolve real assets from free sources, and check source for design tells, providing an evidence loop for improving websites, games, and motion.

A local-first MCP server that enables AI coding assistants to map codebases, transcribe onboarding videos with keyframe screenshots, and maintain structured Obsidian knowledge vaults directly from IDE chat.

Enables AI agents to query a compiler-verified C/C++ knowledge graph built from Coverity build capture, exposing read-only lookups of translation units and their compile flags, entity definitions and fuzzy symbol search, call edges, blast radius, shortest call paths, function-level ASTs, and Coverity defects with checker and severity details.

Write the F**king Manual - Your coding agent writes the user docs from your codebase, screenshots included.

Enables intelligent image analysis using GLM-4.5V model, specializing in extracting and analyzing code from screenshots with support for file paths and clipboard input.

Enables AI coding assistants to connect to local Chrome/Edge sessions for navigation, interaction, screenshots, DOM snapshots, JavaScript evaluation, real-time runtime telemetry, and click-to-component source mapping.

Enables interaction with SAP ABAP systems via ADT APIs, allowing management of ABAP objects, transport requests, and code analysis through MCP clients.

Enables agents and terminals to reverse engineer native binaries, JavaScript/Electron apps, .NET assemblies, and websites, returning findings with supporting evidence and stated limitations. Analysis runs locally, so users can investigate features without source code, explain how they work, and build comparable implementations.

Enables coding agents to query a codebase's git-history coupling graph to find blast radius, missing coupled files, explain why files change together via PRs/issues, and report how much of the graph was inspected.

MCP server that performs mutation testing and diff scoping to score how trustworthy tests are for detecting regressions in changed code.

Connects coding agents to local analysis tools that inspect native binaries, JavaScript/Electron apps, .NET assemblies, and websites, returning findings with supporting evidence and stated limitations. This lets an agent explain how an existing feature works without source code and then build an equivalent implementation for the user's own project.

Helps AI read GitHub repository structure and important files. Want to quickly understand what a repo is about? Prompt it with "read https://github.com/adhikasp/mcp-git-ingest and determine how the code technically works".

Enables AI agents (and a matching CLI) to inspect native binaries, JavaScript/Electron apps, .NET assemblies, Go/Rust/WASM artifacts, EVM bytecode, SQLite databases, recorded crashes, and websites without source code, explaining how features work and returning the evidence and limitations behind each conclusion. Analysis runs locally, using optional Hopper, Ghidra, or IDA providers for native targets.

Tells you how you and your Claude agent actually work together. Reads CLAUDE.md, hooks, skills, memory + scheduled tasks and writes you a letter. Local-only, no API keys, no data leaves your machine.

Enables AI agents to drive Ghidra for static malware analysis, including decompilation, renaming, cross-referencing, and annotated screenshot evidence capture.

MCP server for code and UI safety: provides blast-radius analysis, breaking-change detection, headless UI capture and diffing, and checkpoint/rollback for workspaces.

Connects AI coding agents to the RenderDoc GUI so they can read the capture already open there — the selected event, pipeline state, shaders, bound resources, buffers, render targets and pixel values — for evidence-based rendering debugging. Inspection is read-only, so agents never need to reopen the capture or change the event you have selected, and multiple agents can share one session.

Enables agents to generate a JSON sitemap of how a path through a TypeScript/JavaScript codebase runs, capturing the summary, areas, every step with its file, lines, description, calls and data, and the links between services. The resulting document can be opened in a viewer that draws the same map as a single page, and rebuilt in CI to keep system documentation current.

MCP server for developing Quickshell widgets that lets AI agents render individual widgets to PNG previews offscreen, without screen capture or affecting the live shell.

Enables AI coding assistants to scan an iOS, Android, Flutter, React Native or Expo project for App Store and Google Play rejection risks, returning deterministic findings that cite the guideline section, link to the official Apple or Google page and explain how to fix each problem. Nothing leaves the machine and no AI is used in the checks.