A
licenseA
qualityD
maintenanceAn MCP server that converts PDF files to Markdown format using AI sampling capabilities, supporting both local files and URLs with incremental conversion features.
Last updated
1
1
MIT
pymupdf4llm-mcp
by ai-zerolab
Integrates with Codecov for code coverage reporting and tracking of the project's test coverage metrics.
Provides integration with GitHub through repository links, documentation hosting, and development workflows.
Enables conversion of PDF documents to Markdown format, optimized for processing by large language models.
Displays project status badges for release versions, build status, code coverage, commit activity, and license information.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@pymupdf4llm-mcpconvert this PDF to markdown for analysis"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
This package has been merged into official repo, please use the official repo instead.
https://github.com/pymupdf/pymupdf4llm-mcp
pymupdf4llm-mcp
MCP Server for pymupdf4llm, best for export PDF to markdown for LLM.
Github repository: https://github.com/ai-zerolab/pymupdf4llm-mcp/
Documentation https://ai-zerolab.github.io/pymupdf4llm-mcp/
Quick Start
Run the following command to run the MCP server:
uvx pymupdf4llm-mcp@latest stdio # stdio mode
# or
uvx pymupdf4llm-mcp@latest sse # sse modeConfigure your cursor/windsurf/... and other MCP client to this server:
{
"mcpServers": {
"pymupdf4llm-mcp": {
"command": "uvx",
"args": [
"pymupdf4llm-mcp@latest",
"stdio"
],
"env": {}
}
}
}Maintenance
–Maintainers
–Response time
–Release cycle
–Releases (12mo)
Commit activity
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Tools
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- Alicense-qualityAmaintenanceMCP server that reads PDFs and exposes them as structured Markdown, metadata, outlines, images, and tables to LLM consumers via tools like pdf_read_markdown and pdf_info.Last updatedApache 2.0
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