📄 ParseFlow

Universal document parsing library for PDF, Word, and Excel files

ParseFlow is a comprehensive document parsing solution that supports PDF, Word (docx), and Excel (xlsx/xls) files. It provides both a standalone library and an MCP (Model Context Protocol) server for AI assistants.

中文文档 | Examples | GitHub

✨ Features

📄 PDF Support

✅ Text extraction with multiple strategies (raw, formatted, clean)
✅ Page-specific and range-based extraction
✅ Metadata retrieval (title, author, dates, page count)
✅ Full-text search with context
✅ Image extraction (placeholder)
✅ Table of contents (TOC) extraction (placeholder)

📝 Word (docx) Support

✅ Text extraction
✅ HTML conversion
✅ Metadata retrieval
✅ Text search with context

📊 Excel (xlsx/xls) Support

✅ Multi-sheet data extraction
✅ Multiple output formats (JSON, CSV, Text)
✅ Sheet-specific extraction
✅ Cell-based search
✅ Range extraction
✅ Workbook metadata

🤖 MCP Server

✅ 9 tools for AI assistants (5 PDF + 2 Word + 2 Excel)
✅ Works with Claude Desktop and other MCP clients
✅ Path security with allowlist support

📦 Installation

Core Library

npm install parseflow-core

MCP Server (Global)

npm install -g parseflow-mcp-server

Or use with npx:

npx parseflow-mcp-server

🚀 Quick Start

PDF Parsing

import { PDFParser } from 'parseflow-core';

const parser = new PDFParser();

// Extract all text
const text = await parser.extractText('document.pdf');

// Extract specific page
const page5 = await parser.extractPage('document.pdf', 5);

// Search
const results = await parser.search('document.pdf', 'keyword');

// Get metadata
const metadata = await parser.getMetadata('document.pdf');

Word Parsing

import { WordParser } from 'parseflow-core';

const parser = new WordParser();

// Extract text
const result = await parser.extractText('report.docx');
console.log(result.text);

// Convert to HTML
const html = await parser.extractHTML('report.docx');

// Search
const matches = await parser.searchText('report.docx', 'budget');

Excel Parsing

import { ExcelParser } from 'parseflow-core';

const parser = new ExcelParser();

// Extract all sheets (JSON format)
const data = await parser.extractData('spreadsheet.xlsx');

// Extract specific sheet
const sales = await parser.extractData('data.xlsx', {
  sheetName: 'Q4 Sales',
  format: 'json'
});

// Search in cells
const results = await parser.searchText('data.xlsx', 'revenue');

🛠️ MCP Server Usage

Configuration for Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "parseflow": {
      "command": "npx",
      "args": ["-y", "parseflow-mcp-server"],
      "env": {
        "PARSEFLOW_ALLOWED_PATHS": "C:\\Documents;D:\\Projects"
      }
    }
  }
}

Available Tools

PDF Tools

extract_text - Extract text from PDF files
search_pdf - Search for keywords in PDF
get_metadata - Get PDF metadata
extract_images - Extract images from PDF
get_toc - Get table of contents

Word Tools

extract_word - Extract text/HTML from Word documents
search_word - Search in Word documents

Excel Tools

extract_excel - Extract data from Excel spreadsheets
search_excel - Search in Excel cells

Example Usage in Claude

"请读取 report.docx 文件的内容"
→ Uses extract_word tool

"在 sales.xlsx 中查找 '产品A'"
→ Uses search_excel tool

"提取 document.pdf 的元数据"
→ Uses get_metadata tool

📚 Documentation

Office Examples - Word and Excel usage examples
Release Guide - How to publish new versions
Contributing - Contribution guidelines
Security Policy - Security vulnerability reporting
Code of Conduct - Community guidelines

🏗️ Project Structure

ParseFlow/
├── packages/
│   ├── pdf-parser-core/      # Core library (parseflow-core)
│   │   ├── src/
│   │   │   ├── parser.ts     # PDF parser
│   │   │   ├── WordParser.ts # Word parser
│   │   │   └── ExcelParser.ts # Excel parser
│   │   └── package.json
│   └── mcp-server/           # MCP server (parseflow-mcp-server)
│       ├── src/
│       │   ├── index.ts      # Server entry
│       │   └── tools/        # MCP tools
│       └── package.json
├── docs/                     # Documentation
├── examples/                 # Usage examples
├── tests/                    # Test files
└── scripts/                  # Build scripts

🧪 Testing

# Run all tests
pnpm test

# Test coverage
pnpm test:coverage

# Run specific test
pnpm test parser.test.ts

Test Files

Word测试文件.docx - Word test document
Excel测试文件.xlsx - Excel test workbook (3 sheets)
PDF测试文档.pdf - PDF test document

🔧 Development

# Install dependencies
pnpm install

# Build all packages
pnpm build

# Watch mode
pnpm dev

# Lint
pnpm lint

# Type check
pnpm type-check

📈 Roadmap

v1.1.0 (Current)

✅ Word (docx) support
✅ Excel (xlsx/xls) support
✅ 9 MCP tools

v1.2.0 (Planned)

Encrypted PDF support
OCR text recognition
PowerPoint (pptx) support
Batch processing optimization

v2.0.0 (Future)

Plugin system
More document formats (CSV, TXT, RTF)
Advanced table extraction
Document conversion

🤝 Contributing

We welcome contributions! Please see CONTRIBUTING.md for details.

Ways to Contribute

🐛 Report bugs
💡 Suggest features
📝 Improve documentation
🔧 Submit pull requests

📦 Packages

Package	Version	Description
parseflow-core	1.0.1	Core parsing library
parseflow-mcp-server	1.0.2	MCP server for AI

🔗 Links

npm Core: https://www.npmjs.com/package/parseflow-core
npm MCP: https://www.npmjs.com/package/parseflow-mcp-server
GitHub: https://github.com/Libres-coder/ParseFlow
Issues: https://github.com/Libres-coder/ParseFlow/issues
MCP Registry: https://registry.modelcontextprotocol.io/

📄 License

MIT License - see LICENSE file for details.

🙏 Acknowledgments

pdf-parse - PDF parsing
pdf-lib - PDF manipulation
mammoth - Word document parsing
xlsx - Excel spreadsheet parsing
MCP SDK - Model Context Protocol

📊 Stats

Test Coverage: 83%+
Supported Formats: 3 (PDF, Word, Excel)
MCP Tools: 9
Dependencies: Minimal and well-maintained

💬 Community

Issues: GitHub Issues
Discussions: GitHub Discussions

Made with ❤️ by Libres-coder

Status: 🎉 Production Ready (v1.1.0)

parseflow

Documentation