microsoft/markitdown
MarkItDown is a Python tool that converts various file formats into Markdown and integrates with LLM applications via an MCP server for enhanced text analysis and document processing.
Awesome MCP › Other MCP Servers
0xshellming/mcp-summarizer
MCP Content Summarizer Server is a Model Context Protocol server that adds content summarization to any MCP client, using the Google Gemini 1.5 Pro model to generate the summaries. The README states that the summarization service behind it is powered by 3MinTop, a reading tool aimed at conveying the content of a chapter in about three minutes. The server exposes a single main tool named summarize. It accepts a content argument that may be a plain text string, a URL for a web page, a base64 encoded PDF or the contents of an EPUB file, together with a type argument declaring which of text, url, pdf or epub was supplied. Optional arguments shape the output: maxLength caps the summary in characters and defaults to 200, language selects the target language and defaults to English, focus names a specific aspect the summary should concentrate on, and style chooses between concise, detailed and bullet-points. HTML content is listed among the supported input formats, and the project describes smart context preservation so key information survives compression. A second, demonstrative feature is a dynamic greeting resource addressed as greeting://{name}, which returns a greeting for the supplied name and exists to illustrate basic MCP resource functionality rather than to do useful work. The project is written in TypeScript, built and run with pnpm through install, build and start scripts, with a watch mode for development and server behaviour customizable by editing src/index.ts. Integration with a desktop MCP client is a mcpServers entry that runs node against the built dist/index.js file with an absolute path. The code is MIT licensed. It suits users who want an assistant to condense long documents, articles or books into short summaries in a chosen language without building their own summarization pipeline.
https://github.com/0xshellming/mcp-summarizer
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