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

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

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

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 -

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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.

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.

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.

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.

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

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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 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

A personal filesystem that works as your life operating system — designed to be read, queried, and operated on by an AI agent. Life OS is a structured set of markdown files that give an AI agent (Goose, Claude, or any LLM with filesystem access via MCP) persistent context about your life — who you are, what you're working on, what you're learning, and what's happened. The AI reads these files at t

An MCP server that analyzes order book depth and imbalance across major crypto exchanges, empowering AI agents and trading systems with real-time market structure insights. - Order Book Metrics: Calculate bid/ask depth and imbalance for a specified trading pair on a given exchange. - Cross-Exchange Comparison: Compare order book depth and imbalance across multiple exchanges in a unified Markdown t

Update properties or content across many pages in a Notion database with dry-run and error recovery

An MCP server that delivers real-time cross-chain bridge rates and optimal transfer routes to support decision-making by onchain AI agents. - Get Bridge Rates: Retrieve cross-chain bridge rates for token pairs, including USD values, gas costs, route providers and tags, presented in a Markdown table. - List Supported Chains: Fetch a sorted list of blockchain networks supported by LI.FI. - List Supp

A Model Context Protocol (MCP) server that implements the Zettelkasten knowledge management methodology, allowing you to create, link, explore and synthesize atomic notes through Claude and other MCP-compatible clients. The Zettelkasten method is a knowledge management system developed by German sociologist Niklas Luhmann, who used it to produce over 70 books and hundreds of articles. It consists

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

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