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

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

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

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

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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.

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.

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.

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 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

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

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 provides real-time whale alerts on Hyperliquid, flagging positions with a notional value exceeding $1 million. - Tool: getwhalealerts: Fetches recent whale transactions and returns them as a Markdown table using pandas for clean formatting. - Prompt: summarizewhaleactivity: Generates a summary of whale transactions, including metrics like total position value and notable symbols

You are an expert Python developer with extensive experience in Temporal.

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 -

An MCP server application that sends various types of messages to the WeCom group robot. To install mcp-wecombot-server for Claude Desktop automatically via Smithery: Send a text message to WeCom group - sendmarkdown Send a markdown message to WeCom group - sendimage Send an image message to WeCom group Send a news message to WeCom group,a news include title,description,url,picurl - sendtemplateca

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 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

An MCP server that provides cryptocurrency project data from Mobula.io to AI agents. - Fetch Project Data: Retrieve comprehensive project details (e.g., market data, tokenomics, and links) from Mobula. - Structured Output: Format project data into a well-organized Markdown document with sections for overview, market data, investors, exchanges, token distribution, and release schedules. - Language

Packages generated wiki Markdown into a VitePress static site with dark theme, dark-mode Mermaid diagrams with click-to-zoom, and production build output. Use when the user wants to create a browsable website from generated wiki pages.

A FastMCP server that allows querying Loki logs from Grafana. - GRAFANAURL: URL of your Grafana instance - GRAFANAAPIKEY: Grafana API key with appropriate permissions - Query Loki logs through Grafana API - Get Loki labels and label values - Format query results in different formats (text, JSON, markdown) - Support for both stdio and SSE transport protocols - Python 3.10+ 1. Clone this repository