Markdown AI Agent Skills

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 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

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

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。

An MCP server that delivers crypto ETF flow data to power AI agents' decision-making. - Unified Tool: The getetfflow tool dynamically fetches historical ETF flow data for BTC or ETH. - Markdown Table Output: Leverages pivot tables to present data with ETF tickers as columns, dates as rows, and a total column for summed flows. - Prompt Guidance: Includes a prompt (etfflowprompt) to streamline LLM i

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

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

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.

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

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