"Using YouTube to obtain and summarize video content" matching MCP servers:

Enables local analysis of OpenAPI 3 and Swagger 2 JSON/YAML spec files on disk, with no remote fetching of specs or credentials. It groups endpoints by tag, flags operations that appear to lack security, lists deprecated operations, and produces short markdown cheat sheets for agents.

Enables interaction with Prismic through tools for reading documents, managing media assets, and performing content migrations or updates. Supports the Prismic Content, Asset, Migration, and Custom Types APIs with secure write operations and multi-transport support.

An MCP server that uses AI to generate structured Asana project plans from diverse sources like text, PDFs, and meeting transcripts. It enables users to preview, generate, and directly sync detailed task lists, subtasks, and dependencies into Asana.

Enables AI assistants to interact directly with Strapi v5 CMS content through full CRUD operations, media uploads, and content type exploration using Strapi's Document Service API.

Enables management of WordPress posts and pages including creating, updating, deleting, duplicating, scheduling, and bulk editing content through the WordPress REST API.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

MCP server for AI agents to send notifications, copy to clipboard, request confirmations, and collect text input from users across their devices.

Routes one brief to the right image model across 60+ (gpt-image-1.5, Ideogram 3, Recraft V4, Flux), validates the output, and fans out to iOS/Android/PWA/favicon/visionOS/Flutter bundles. Works without an API key via Pollinations, HF Inference, Stable Horde, or host-LLM inline SVG.

Enables users to turn any API's documentation into a tested MCP server whose tools expose the API's own operations, with linting, contract tests, and live verification. It accepts OpenAPI/Swagger, Postman, RAML, WSDL, GraphQL, RSS, and HTML docs.

Enables turning requirements documents into RFCs, functional test scenarios, and a traceability matrix, with tools to parse, diff, and verify coverage.

Enables AI models to interact with IBM FileNet Content Manager for document management, folder operations, metadata handling, search, and content extraction through a standardized interface.

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

A Model Context Protocol server that converts Markdown content to HTML format.

An MCP server that provides access to project files and their contents, allowing users to retrieve file data from specified project directories with error handling and configuration options.

A professional video format conversion tool based on MCP protocol that supports multiple formats, batch processing, and quality control for video files.

Enables AI-driven batch refactoring of Movable Type content via the MT Data API using natural language instructions. It provides a secure workflow featuring automated backups, visual diff reports, and rollback capabilities for safe HTML transformations.

Enables an MCP-compatible AI client to author Blender Python, run Blender, import the resulting asset into Unity with materials and a prefab, place it in the active scene, verify the import, and revise the same asset using stable IDs.

Enables AI assistants to query PostgreSQL, MySQL, SQL Server, Oracle, and MongoDB databases through MCP with read-only, audited access.

Generates standalone, human-readable MCP servers from RAML 1.0 or OpenAPI 3.x specs, exposing one tool per resource and method that makes real HTTP calls. It understands Mule/Anypoint auth patterns such as Client ID enforcement and OAuth2, wiring the expected credentials from environment variables at call time.