"Tor Project" matching MCP servers:

Enables fetching, searching, and summarizing YouTube video transcripts with multi-language support.

Extracts and summarizes learning content from YouTube videos, PDFs, and web articles to provide context for project-based learning. It features automated background processing and integrates with Forest's HTA builder for informed task generation.

Provides tools to summarize README files from local paths or public Git repositories into structured JSON summaries. It enables users to quickly extract key facts and project overviews from documentation through automated tool calls.

Enables AI agents to search, watch, summarize, clip, and extract transcripts from YouTube videos, all without needing an API key or leaving the chat.

A Model Context Protocol (MCP) server that automates generating LinkedIn post drafts from YouTube videos. This server provides high-quality, editable content drafts based on YouTube video transcripts.

Enables intelligent Markdown document analysis including extracting table of contents with hierarchy, detecting numbering issues like duplicates and discontinuities, and generating formatted TOC content in multiple output formats.

MCP server that converts PDF, video, web, and audio inputs into structured Markdown notes with support for checkpointing, batch processing, and Obsidian integration.

A local-first Codex plugin that bundles an MCP server to safely interact with Mattermost, enabling channel/thread summarization, conversation search, and reviewed post publishing via the Mattermost REST API.

A Python-based MCP server adapted from the n8n_agent project that implements a note storage and summarization system. It enables users to create, retrieve, and summarize notes through the Model Context Protocol.

Enables Claude to read, rewrite, generate, and summarize LibreOffice Writer documents with preview-then-apply editing through MCP tools, authenticating via Claude Code login.

This MCP server enables AI assistants to perform calculations, fetch live weather, manage in-memory notes, access system info and note resources, and use reusable code review and summarization prompts.