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  1. Home
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  3. Huoshui Pdf Converter
Huoshui Pdf Converter logo
Health: ActiveRecent health check succeeded.Last checked 9/7/2026, 8:30:35 PM

Huoshui Pdf Converter

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time β€” check back soon.
View RepositoryVisit Website

An MCP server that provides PDF file conversion

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "huoshui-pdf-converter": {
      "command": "uvx",
      "args": [
        "huoshui-pdf-converter"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Tool Schemas (4) Directory Badge Claim listing AlternativesπŸ’» More in Developer Tools

Capabilities & Tool Schemas (4) ~49 tokensApproximate context cost of this server’s tool schemas (~4 chars/token), before any tool is called. Actual usage depends on your client and model.Self-reported Self-reportedParsed from the repository README, not verified against a live server β€” may be incomplete or out of date.

Inspect callable tools, capabilities, and parameters exposed to AI agents by Huoshui Pdf Converter.

pdf_to_markdown

Convert PDF files to Markdown

markdown_to_pdf

Convert Markdown files to PDF

list_supported_formats

Get supported formats and engines

validate_file

Validate input files before conversion

Documentation Overview

ζ΄»ζ°΄ PDF 转捒器 (Huoshui PDF Converter)

License: MIT Python 3.10+ MCP PyPI version

A high-quality, cross-platform PDF ↔ Markdown converter implemented as an MCP (Model Context Protocol) server. Supports bidirectional conversion with full Unicode/CJK character support.

Features

Core Capabilities

  • PDF β†’ Markdown: Extract text and images with layout preservation
  • Markdown β†’ PDF: Generate beautiful PDFs with multiple rendering engines
  • Unicode Support: Full support for Chinese, Japanese, Korean, and other Unicode characters
  • Cross-Platform: Works on Windows, macOS, and Linux
  • MCP Integration: Use with Claude Desktop or any MCP-compatible client

Technical Features

  • Pure Python: No external system dependencies required
  • Automatic Font Detection: Finds and uses system Unicode fonts
  • Smart Engine Selection: Automatically switches engines based on content
  • Comprehensive Error Handling: Graceful degradation and detailed logging
  • Async Architecture: Non-blocking operations for better performance

Installation

From MCP Registry (Recommended)

This server is available in the Model Context Protocol Registry. Install it using your MCP client.

mcp-name: io.github.huoshuiai42/huoshui-pdf-converter

As a Python Package

Terminal
pip install huoshui-pdf-converter

Or using uv (recommended):

bash
uv pip install huoshui-pdf-converter

As an MCP Server

Add to your Claude Desktop configuration:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json Linux: ~/.config/Claude/claude_desktop_config.json

config.json
{
  "mcpServers": {
    "huoshui-pdf-converter": {
      "command": "uvx",
      "args": ["huoshui-pdf-converter"],
      "env": {}
    }
  }
}

Or if you prefer to use a specific Python environment:

config.json
{
  "mcpServers": {
    "huoshui-pdf-converter": {
      "command": "python",
      "args": ["-m", "huoshui_pdf_converter.server"],
      "env": {}
    }
  }
}

Usage

Command Line Interface

bash
# Convert PDF to Markdown
huoshui-pdf pdf-to-md input.pdf output.md

# Convert Markdown to PDF
huoshui-pdf md-to-pdf input.md output.pdf

# With options
huoshui-pdf md-to-pdf input.md output.pdf --page-size A4 --margin 2cm --font-size 12

As a Python Library

server.ts
import asyncio
from huoshui_pdf_converter import PDFToMarkdownConverter, MarkdownToPDFConverter

async def main():
    # PDF to Markdown
    pdf_converter = PDFToMarkdownConverter()
    result = await pdf_converter.convert(
        pdf_path="input.pdf",
        output_path="output.md",
        extract_images=True,
        preserve_formatting=True
    )

    # Markdown to PDF
    md_converter = MarkdownToPDFConverter()
    result = await md_converter.convert(
        markdown_path="input.md",
        output_path="output.pdf",
        page_size="A4",
        margin="2cm",
        font_size=12
    )

asyncio.run(main())

MCP Tools

When used as an MCP server, the following tools are available:

  1. pdf_to_markdown: Convert PDF files to Markdown

    config.json
    {
      "pdf_path": "path/to/input.pdf",
      "output_path": "path/to/output.md",
      "extract_images": true,
      "preserve_formatting": true
    }
    
  2. markdown_to_pdf: Convert Markdown files to PDF

    config.json
    {
      "markdown_path": "path/to/input.md",
      "output_path": "path/to/output.pdf",
      "page_size": "A4",
      "margin": "2cm",
      "font_size": 12
    }
    
  3. list_supported_formats: Get supported formats and engines

  4. validate_file: Validate input files before conversion

Supported Formats

Input Formats

  • PDF: All standard PDF files (PDF 1.0 - 1.7)
  • Markdown: CommonMark and GitHub Flavored Markdown

Output Options

  • Page Sizes: A4, A3, Letter, Legal
  • Margins: Customizable (e.g., "1cm", "0.5in")
  • Font Sizes: Any size in points
  • Images: PNG, JPEG extraction from PDFs

Unicode and Font Support

The converter automatically detects and uses appropriate fonts for different languages:

  • macOS: Arial Unicode, PingFang SC, STHeiti
  • Windows: Microsoft YaHei, SimSun, Arial Unicode MS
  • Linux: Noto Sans CJK, Source Han Sans, WenQuanYi

Architecture

Conversion Engines

PDF β†’ Markdown

  • PyMuPDF (MuPDF): High-quality text and image extraction

Markdown β†’ PDF

  • ReportLab: Best Unicode support, cross-platform compatibility
  • xhtml2pdf: Good HTML/CSS rendering (fallback)
  • fpdf2: Basic PDF generation (last resort)

Engine Selection Logic

  1. Detects CJK characters β†’ Uses ReportLab
  2. Complex formatting β†’ Uses xhtml2pdf
  3. Basic documents β†’ Uses any available engine

Development

Setup Development Environment

bash
# Clone the repository
git clone https://github.com/yourusername/huoshui-pdf-converter.git
cd huoshui-pdf-converter

# Install dependencies
uv pip install -e ".[dev]"

# Run tests
python test_converter.py

Project Structure

Code
huoshui-pdf-converter/
β”œβ”€β”€ huoshui_pdf_converter/
β”‚   β”œβ”€β”€ __init__.py
β”‚   β”œβ”€β”€ server.py           # MCP server implementation
β”‚   β”œβ”€β”€ pdf_converter.py    # PDF to Markdown converter
β”‚   └── markdown_converter.py # Markdown to PDF converter
β”œβ”€β”€ pyproject.toml
β”œβ”€β”€ README.md
β”œβ”€β”€ LICENSE
└── test_converter.py

Troubleshooting

Common Issues

  1. Chinese characters not displaying:

    • Ensure Arial Unicode or similar fonts are installed
    • The converter will automatically detect and use appropriate fonts
  2. Import errors:

    • Install all dependencies: pip install huoshui-pdf-converter[all]
  3. MCP connection issues:

    • Check Claude Desktop logs
    • Ensure Python is in your PATH

Logging

Enable debug logging:

server.ts
import logging
logging.basicConfig(level=logging.DEBUG)

Contributing

Contributions are welcome! Please:

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

  • Built with FastMCP for Model Context Protocol support
  • Uses PyMuPDF for PDF parsing
  • Uses ReportLab for PDF generation
  • Inspired by the need for better PDF ↔ Markdown conversion tools

Support

  • Issues: GitHub Issues
  • Discussions: GitHub Discussions
  • Email: your.email@example.com

Read the full README β†’View source on GitHub β†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks β€” not a rating.

Last commit
12mo ago
Most recent push to the default branch.
Tools exposed
4
Callable tools this server registers over MCP.

Reviews

No reviews yet β€” be the first to share how this listing worked for you.

Frequently Asked Questions about Huoshui Pdf Converter

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "huoshui-pdf-converter": { "command": "npx", "args": ["-y", "huoshui-pdf-converter"] } }

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Technical Specs & Signals

CategoryπŸ’»Developer Tools
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimePython
Last updatedSep 9, 2025
Views0
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars0
GitHub Star CountTotal stargazers on GitHub representing community popularity (0 stars).
Last commit12mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Sep 9, 2025
44Quality signal: Fair Β· 44/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools23/30
Adoption & activity0/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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