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"Using YouTube to obtain and summarize video content" matching MCP servers:
- Alicense-qualityAmaintenanceTurns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.1MIT
- Alicense-qualityCmaintenanceEnables automated migration of Vue projects to React with intelligent analysis, task management, and learning from user modifications.145MIT
- AlicenseBqualityCmaintenanceEnables 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.4MIT
- AlicenseAqualityBmaintenanceConverts vector PDF circuit schematics into evidence-preserving SchematicIR JSON with tools to inspect, convert, and validate schematic PDFs.3MIT
- FlicenseAqualityDmaintenanceEnables 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.9
- Alicense-qualityCmaintenanceEnables 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.55244MIT
- AlicenseAqualityCmaintenanceEnables blazingly fast file and content searching in large codebases using ripgrep, with intelligent filtering, fuzzy finding, and directory tree visualization while respecting .gitignore and avoiding common bloat directories.4292MIT
- MIT
- FlicenseBqualityCmaintenanceAn MCP server for analyzing Robot Framework test results. It provides LLMs with tools to parse, summarize, and search through test execution logs from XML or JSON output files.32
- AlicenseCqualityCmaintenanceEnables interaction with SAP ABAP systems via ADT APIs, allowing management of ABAP objects, transport requests, and code analysis through MCP clients.10086MIT
HawkeyeAIBridgeofficial
Flicense-qualityAmaintenanceMCP server for fast local code & content search powered by Hawkeye. Enables AI assistants to search indexed codebases & assets with natural language queries.2- Alicense-qualityBmaintenanceBridges local LLMs running in LM Studio with MCP clients like Claude Desktop to perform reasoning and analysis tasks while keeping sensitive data private. It features a suite of tools for local code review, privacy scanning, and content transformation using auto-discovered local models.MIT
- Alicense-qualityDmaintenanceThis MCP server enables AI assistants to interact with decomp.me for video game decompilation projects, providing tools to fetch scratches, compile code, analyze diffs, search contexts, and iterate on improvements.2GPL 3.0
- Alicense-qualityDmaintenanceA Model Context Protocol server that wraps the Gemini CLI, enabling AI assistants to send prompts, research topics, analyze code, and summarize content using Gemini.11MIT
CodeNav MCPofficial
Flicense-qualityBmaintenanceCodeNav MCP is a remote Model Context Protocol server for exploring a codebase, exposing tools to list files, read source, search text, inspect imports/exports, find functions/classes, detect unused code, and summarize project structure.4- Alicense-qualityDmaintenanceAn MCP server that fixes, validates, and generates visual text content for AI coding assistants.MIT
- Alicense-qualityDmaintenanceAn MCP server that provides code search capabilities for AI tools and LLMs using Zoekt, allowing for searching across codebases with advanced query syntax and content fetching.22MIT
- Alicense-qualityDmaintenanceMCP server exposing Sourcegraph's AI-enhanced code search capabilities to coding agents, enabling advanced code search, repository discovery, and content fetching.MIT
- Flicense-qualityDmaintenanceAn MCP server implementing the TRUE Recursive Language Model technique for managing large context windows in Claude Code, enabling analysis of codebases beyond 200k tokens by storing content as variables and using LLM-generated code for search and analysis.