What is the PDF2MD MCP server?

PDF2MD is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.

How do MCP servers relate to agent skills?

Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.

How are reviews shown for PDF2MD?

This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.

ai-mlproductivity

PDF2MD▌

by gavinhuang

Convert PDF to Markdown quickly with PDF2MD — incremental processing that resumes from page markers. Supports local file

Converts PDF files to Markdown format with incremental processing that resumes from existing page markers, supporting both local files and URLs with fallback handling for various content extraction scenarios.

github stars

★ 1

GitHub npm

Incremental processing with resume capabilitySupports both local and remote PDFs

best for

/ Content creators converting documents to Markdown
/ Developers processing PDF documentation
/ Data extraction from PDF reports

capabilities

/ Convert PDF files to Markdown using AI extraction
/ Process PDFs from local file paths or URLs
/ Resume conversion from existing page markers
/ Configure custom output directories
/ Handle various PDF content extraction scenarios

what it does

Converts PDF files to Markdown format using AI, supporting both local files and URLs with incremental processing that can resume from existing progress.

about

PDF2MD is a community-built MCP server published by gavinhuang that provides AI assistants with tools and capabilities via the Model Context Protocol. Convert PDF to Markdown quickly with PDF2MD — incremental processing that resumes from page markers. Supports local file It is categorized under ai ml, productivity. This server exposes 1 tool that AI clients can invoke during conversations and coding sessions.

how to install

You can install PDF2MD in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

PDF2MD is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

PDF2MD MCP Server

An MCP (Model Context Protocol) server that converts PDF files to Markdown format using AI sampling capabilities.

Features

Convert PDF files to Markdown using AI content extraction
Support for both local file paths and URLs
Incremental conversion - resume from where you left off
Configurable output directory
Built with FastMCP for high performance

Installation

pip install pdf2md-mcp

Usage

As an MCP Server

Start the server:

pdf2md-mcp

The server will expose MCP tools for PDF to Markdown conversion.

Available Tools

`convert_pdf_to_markdown`

Converts a PDF file to Markdown format using AI sampling.

Parameters:

file_path (string): Local file path or URL to the PDF file
output_dir (string, optional): Output directory for the markdown file. Defaults to the same directory as input file (for local files) or current working directory (for URLs)

Returns:

output_file: Path to the generated markdown file
summary: Summary of the conversion task
pages_processed: Number of pages processed

Requirements

Python 3.10+
An MCP-compatible client with AI sampling capabilities
Network access for URL-based PDF files

Development

Setup

git clone https://github.com/shuminghuang/pdf2md-mcp.git
cd pdf2md-mcp
pip install -e ".[dev]"

Running Tests

pytest

Code Formatting

black .
isort .

License

MIT License - see LICENSE file for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

FAQ

What is the PDF2MD MCP server?: PDF2MD is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?: Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for PDF2MD?: This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.

MCP server reviews

Ratings

4.5★★★★★10 reviews

★★★★★Shikha Mishra· Oct 10, 2024
PDF2MD is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
★★★★★Piyush G· Sep 9, 2024
We evaluated PDF2MD against two servers with overlapping tools; this profile had the clearer scope statement.
★★★★★Chaitanya Patil· Aug 8, 2024
Useful MCP listing: PDF2MD is the kind of server we cite when onboarding engineers to host + tool permissions.
★★★★★Sakshi Patil· Jul 7, 2024
PDF2MD reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
★★★★★Ganesh Mohane· Jun 6, 2024
I recommend PDF2MD for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
★★★★★Oshnikdeep· May 5, 2024
Strong directory entry: PDF2MD surfaces stars and publisher context so we could sanity-check maintenance before adopting.
★★★★★Dhruvi Jain· Apr 4, 2024
PDF2MD has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
★★★★★Rahul Santra· Mar 3, 2024
According to our notes, PDF2MD benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
★★★★★Pratham Ware· Feb 2, 2024
We wired PDF2MD into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
★★★★★Yash Thakker· Jan 1, 2024
PDF2MD is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.