Markdown AI Agent Skills

The markitdown-mcp package provides a lightweight STDIO, Streamable HTTP, and SSE MCP server for calling MarkItDown. It exposes one tool: converttomarkdown(uri), where uri can be any http:, https:, file:, or data: URI. To install the package, use pip: To run the MCP server, using STDIO (default) use the following command: To run the MCP server, using Streamable HTTP and SSE use the following comma

Format CVs for academic positions with publications, grants, and teaching

MseeP.ai Security Assessment A Model Context Protocol server that provides browser automation capabilities using Playwright. This server enables LLMs to interact with web pages, take screenshots, generate test code, web scrapes the page and execute JavaScript in a real browser environment. Test your web applications on real device profiles with a simple command: Natural Language Support for AI Ass

Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration

The memex Vannevar Bush imagined, built for people who think for a living. I was setting up my OpenClaw agent and started a markdown brain repo. One page per person, one page per company, compiled truth on top, append-only timeline on the bottom. The agent got smarter the more it knew, so I kept feeding it. Meetings, emails, tweets, Apple Notes, calendar data, original ideas. One thing led to anot

Content Core is a powerful, AI-powered content extraction and processing platform that transforms any source into clean, structured content. Extract text from websites, transcribe videos, process documents, and generate AI summaries—all through a unified interface with multiple integration options. Extract content from anywhere: - 📄 Documents - PDF, Word, PowerPoint, Excel, Markdown, HTML, EPUB -

Archive session learnings, debugging solutions, and deployment logs to .archive/yyyy-mm-dd/ as indexed markdown with searchable tags. Use when completing a significant task, resolving a tricky bug, deploying, or when the user says \"archive this\". Maintains .archive/MEMORY.md index for cross-session knowledge reuse.

Repository-grounded threat modeling that enumerates trust boundaries, assets, attacker capabilities, abuse paths, and mitigations, and writes a concise Markdown threat model. Trigger only when the user explicitly asks to threat model a codebase or path, enumerate threats/abuse paths, or perform AppSec threat modeling. Do not trigger for general architecture summaries, code review, or non-security design work.

An MCP server that gives AI agents fast access to verified EVM chain information, including RPC URLs, chain IDs, explorers, and native tokens — sourced from Chainlist.org. - Efficient Data Fetching: Caches Chainlist API data to minimize requests. - Flexible Search: Case-insensitive keyword matching using regex for getChainsByKeyword. - Structured Output: Markdown responses with tabulated rpc and e

Search and retrieve biomedical data — genes, variants, clinical trials, articles, drugs, diseases, pathways, proteins, adverse events, pharmacogenomics, and phenotype-disease matching. 15 sources including PubMed, ClinicalTrials.gov, ClinVar, OncoKB, Reactome, UniProt, PharmGKB, OpenFDA, Monarch. Use when asked about gene function, variant pathogenicity, trial matching, drug safety, resistance mechanisms, hereditary syndromes, or literature evidence.

MCP server for MinerU document parsing API — extract text, tables, and formulas from PDFs, DOCs, and images. - VLM model — 90%+ accuracy for complex documents - Pipeline model — Fast processing for simple documents - Local file upload — Upload files from disk for batch parsing - Batch processing — Parse up to 200 documents at once - Download & rename — Extract markdown with original filenames - Pa

Convert raw notes, error logs, voice dictation, or screenshots into crisp GitHub-flavored markdown issue reports. Use when the user pastes bug info, error messages, or informal descriptions and wants a structured GitHub issue. Supports images/GIFs for visual evidence.

Free Local RAG for Claude Code - Save Tokens & Time 日本語版はこちら | Japanese Version DevRag is a lightweight RAG (Retrieval-Augmented Generation) system designed specifically for developers using Claude Code. Stop wasting tokens by reading entire documents - let vector search find exactly what you need. When using Claude Code, reading documents with the Read tool consumes massive amounts of tokens: - ❌

WP Astro MCP is a Model Context Protocol server that turns WordPress sites into production-ready Astro projects. It connects to your WordPress REST API, extracts everything (posts, pages, CPTs, SEO, ACF, menus, media), converts HTML to clean Markdown, scaffolds a complete Astro project, and pushes to GitHub — all through conversational commands in Claude Code. Migrating WordPress to Astro involves

Convert markdown (.md) files into professional, interactive PDF documents with automatic table of contents. mcp-name: io.github.wmarceau/md-to-pdf - Automatic Table of Contents - Generated from markdown headers - Interactive Navigation - Clickable TOC links to sections - Professional Styling - Clean, readable PDF output - Code Block Support - Syntax highlighting preserved - Table Support - Markdow

文颜（Wenyan） 是一款多平台 Markdown 排版与发布工具，支持将 Markdown 一键转换并发布至： - 以及其它内容平台（持续扩展中） 文颜的目标是：让写作者专注内容，而不是排版和平台适配。 文颜目前提供多种形态，覆盖不同使用场景： - macOS App Store 版 - MAC 桌面应用 - 跨平台桌面版 - Windows/Linux - CLI 版本 - 命令行 / CI 自动化发布 - 👉 MCP 版本 - 本项目 - 核心库 - 嵌入 Node / Web 项目 本仓库是 文颜的 MCP Server 版本，基于模型上下文协议（Model Context Protocol），旨在让 AI 助手（如 Claude Desktop）具备自动排版和发布公众号文章的能力。 - 与 AI 深度集成：让 AI 帮你管理公众号的排版和发布 - 支持 SSE 模式

An MCP server that aggregates real-time cryptocurrency news from multiple RSS feeds, helping AI agents make informed decisions in a fast-paced market. - Feed Retrieval: Fetches latest entries from specified RSS feeds, formatting them as Markdown with plain-text summaries. - Keyword Filtering: Filters feeds by keyword in descriptions or categories. - OPML Support: Import feed list from a local OPML

skill-depot replaces the "dump all skill frontmatter into context" approach with selective, semantic retrieval. Agent skills are stored as Markdown files and indexed with vector embeddings — only the relevant skills are loaded when needed, keeping context lean. - Semantic Search — Find skills by meaning, not just keywords, using embedded vector search - Fully Local — No API keys, no cloud. U

Scrape, crawl, search, and extract web data. Converts any website to LLM-ready markdown. Local-first with smart escalation (HTTP → browser → stealth). No API key needed.

Markdownify is a Model Context Protocol (MCP) server that converts various file types and web content to Markdown format. It provides a set of tools to transform PDFs, images, audio files, web pages, and more into easily readable and shareable Markdown text. - Convert multiple file types to Markdown: - Audio (with transcription) - Convert web content to Markdown: - YouTube video transcripts - Bing

A general purpose Model Context Protocol (MCP) server that provides comprehensive developer tools for file editing, shell command execution, and screen capture capabilities. Built using the rmcp crate. - View files with language detection for markdown formatting - Write/create files with automatic directory creation - String replacement with precise matching - Undo functionality with edit history

Jotdown is a Model Context Protocol (MCP) server that allows large language models (LLMs) to interact with Notion and also generate Markdown Books. It provides two primary tools for LLMs: - 👉 Notion Integration: Create or update pages in Notion with content generated by the LLM. - 👉 Mdbook Generation: Generate a mdbook from content and manage the structure. Jotdown enables LLMs to seamlessly int