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 -

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

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.

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.

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

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

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: - ❌

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.

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

通过 uvx 安装并运行： 安装完成后，直接运行： 运行后你可以直接使用工具，例如： 或（如果是 uvx 安装）： 好的，这是转换后的 Markdown 版本： 好的，这是转换后的 Markdown 版本： 1. 配置环境变量（可选） 你可以通过 .env 文件或系统环境变量配置 DolphinDB 的连接信息： 也可以不设置，系统将使用默认值。 该命令会启动 MCP 插件服务，供外部调用。 3. FastMCP Agent 使用示例 启动后，你的工具将通过 FastMCP 对外暴露以下函数接口： listtbs(dbName: str) querytablediskusage(database: str, tableName: str) querydolphindb(script: str) 可通过 MCP 前端界面或对接 LLM 工具链来进行访问。

A collection of AI agents for various tasks. Welcome to the agents repository! This project contains various AI agent definitions. The definitions can be used by any agentic system that supports markdown. An MCP (Model Context Protocol) server that delivers AI agent instructions on demand from this repository's collection of 42+ specialized agents. The server exposes 3 MCP tools: List all availabl

Fast, token-efficient web content extraction for AI agents - converts websites to clean Markdown. Existing MCP web crawlers are slow and consume large quantities of tokens. This pauses the development process and provides incomplete results as LLMs need to parse whole web pages. This MCP package fetches web pages locally, strips noise, and converts content to clean Markdown while preserving links.

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

An MCP server that tracks and monitors the latest trending tokens on CoinGecko, providing real-time insights into the most popular cryptocurrencies. - Tool: gettrendingmddoc Returns a Markdown document of the full CoinGecko trending page, including a table of trending cryptocurrencies with columns: Rank, Name, Symbol, Price, 1h Change, 24h Change, 7d Change, 24h Volume, Market Cap. - Prompt: parse

Provides score interpretation (< 0.3 good, > 0.5 skip), query optimization, and source naming for query_documents, ingest_file, ingest_data tools. Use this skill when working with RAG, searching documents, ingesting files, saving web content, or handling PDF, HTML, DOCX, TXT, Markdown.

TL;DR for AI agents — enquire-mcp is the 1 Obsidian MCP: a local memory and document-intelligence layer that makes one vault persistently searchable from Claude Code, Claude Desktop, Cursor, ChatGPT, Codex, OpenClaw, and any MCP client. It returns cited source context across Markdown, PDFs + OCR, Canva