MarkGrab
Convert almost any URL—HTML, YouTube, PDF, DOCX—into LLM-ready markdown from your agent via MCP.
Overview
MarkGrab is an MCP server for the Idea phase that converts URLs—including HTML, YouTube, PDF, and DOCX—into LLM-ready markdown.
What is this MCP server?
- Universal extraction: HTML pages, YouTube, PDF, and DOCX URLs to markdown
- LLM-ready markdown output designed for agent context windows
- markgrab PyPI package (0.1.2) with stdio MCP transport
- Reduces manual copy-paste and brittle one-off scrapers during research
- GitHub repository QuartzUnit/markgrab
- MCP server version 0.1.2
- Supports HTML, YouTube, PDF, and DOCX sources per server description
- PyPI identifier markgrab, stdio transport
What problem does it solve?
Research and agent workflows stall when pages, videos, and PDFs arrive as messy HTML or binary blobs instead of clean text you can reason over.
Who is it for?
Builders who constantly pull docs, landing pages, papers, and videos into agent context without writing custom scrapers per format.
Skip if: Workflows that need schema-locked JSON from scanned forms, or teams blocked from fetching arbitrary URLs by compliance policies.
What do I get? / Deliverables
After you connect MarkGrab, your agent can request a URL and receive markdown you can cite, summarize, or drop into build and content tasks.
- LLM-ready markdown from supported URL types (HTML, YouTube, PDF, DOCX)
- Agent-callable extraction without per-site scraper scripts
- Cleaner research corpora for ideation and content pipelines
Recommended MCP Servers
Journey fit
Grabbing readable web and file content is most critical early when you research competitors and docs before locking scope. Research is the primary shelf because MarkGrab’s core job is ingest external URLs into markdown for analysis, even though build teams reuse it for integrations.
How it compares
URL-to-markdown web extraction MCP, not local semantic repo search or curated RSS-only research.
Common Questions / FAQ
Who is markgrab for?
Indie builders and agent users who research on the open web and need consistent markdown from mixed URL types inside MCP clients.
When should I use markgrab?
Use it whenever you have a link to a page, video, PDF, or DOCX and want LLM-ready markdown for analysis, specs, or content without manual cleanup.
How do I add markgrab to my agent?
Install markgrab from PyPI (0.1.2), add the MCP stdio server entry with identifier markgrab, restart your agent host, and invoke extraction tools with target URLs.