Markdown AI Agent Skills

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

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

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: - ❌

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

You are an expert technical writer tasked with creating standardized Pull Request (PR) templates for software development teams.

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 the Notion API, enabling LLM to interact with Notion workspaces. Additionally, it employs Markdown conversion to reduce context size when communicating with LLMs, optimizing token usage and making interactions more efficient. Here is a detailed explanation of the steps mentioned above in the following articles: - English Version: https://dev.to/suekou/operating-notion-via-claude-des

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

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.

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.

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.

Scrapes content based on a preset URL list, filters high-quality technical information, and generates daily Markdown reports.

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A Model Context Protocol (MCP) server for converting Markdown content to interactive mindmaps. Or using uvx: Or using docker safer and easier. Three installation methods have been successfully tested on macOS and Linux. For Windows users experiencing issues with npx for this MCP, consider using the Docker method. Alternatively, if you use Visual Studio Code, the "Markmap" extension offers a potent

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

tip.md is a platform that allows developers to receive cryptocurrency tips directly to their wallets via a simple button embeddable in GitHub READMEs, websites, or any markdown content. It supports: - Multiple Blockchains: Ethereum, Base,Solana, and Bitcoin Lightning Network - Direct-to-Wallet Payments: Tips go straight to your wallet, no custody - Simple Integration: One button, works everywhere

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 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

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.

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

A Model Context Protocol (MCP) server implementation that integrates with Olostep for web scraping, content extraction, and search capabilities. To set up Olostep MCP Server, you need to have an API key. You can get the API key by signing up on the Olostep website. - Scrape website content in HTML, Markdown, JSON or Plain Text (with optional parsers) - Parser-based web search with structured resul

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.

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