document-parser
README.md
# Multi-Format Document Parser MCP Server
[](https://smithery.ai/server/@agenson-horrowitz/document-parser-mcp)
[](https://www.npmjs.com/package/@agenson-horrowitz/document-parser-mcp)
[](https://smithery.ai/server/agenson-horrowitz/document-parser-mcp)
[](https://opensource.org/licenses/MIT)
[](https://modelcontextprotocol.io)
A professional-grade MCP server that provides AI agents with comprehensive document parsing capabilities. Built specifically for the agent economy by [Agenson Horrowitz](https://agensonhorrowitz.cc).
## 🤖 Why This Exists
AI agents constantly receive documents in various formats but need structured text and data. Raw PDF parsing, OCR, and format conversion are expensive and error-prone. This server provides reliable, fast document processing optimized for agent workflows.
## ⚡ Key Features
- **Advanced PDF Parsing**: Extract text, tables, and metadata with layout preservation
- **Intelligent OCR**: Image-to-text with confidence scoring and preprocessing
- **HTML to Markdown**: Clean conversion preserving structure and links
- **Universal Table Extraction**: Extract structured data from any document format
- **Document Summarization**: Configurable summary generation with keyword extraction
- **Agent-Optimized Output**: Fast processing, structured JSON responses
- **Multi-Format Support**: PDF, images, HTML, text files
## 🚀 Installation
### Claude Desktop Configuration
Add to your `claude_desktop_config.json`:
```json
{
"mcpServers": {
"document-parser": {
"command": "npx",
"args": ["@agenson-horrowitz/document-parser-mcp"]
}
}
}
```
### Cline Configuration
Add to your Cline MCP settings:
```json
{
"mcpServers": {
"document-parser": {
"command": "npx",
"args": ["@agenson-horrowitz/document-parser-mcp"]
}
}
}
```
### Via npm
```bash
npm install -g @agenson-horrowitz/document-parser-mcp
```
### Via MCPize (One-click deployment)
Deploy instantly on [MCPize](https://mcpize.com/mcp/document-parser) with built-in billing and authentication.
## 🛠️ Available Tools
### 1. `parse_pdf`
Extract comprehensive information from PDF documents.
**Perfect for**: Reports, invoices, contracts, research papers, forms
**Features**:
- Text extraction with layout preservation
- Metadata extraction (title, author, creation date, page count)
- Table detection and structured extraction
- Page range processing for large documents
- Reading time estimation and word counts
**Example**:
```json
{
"file_path": "/path/to/document.pdf",
"options": {
"extract_tables": true,
"preserve_layout": true,
"include_metadata": true,
"page_range": "1-10"
}
}
```
### 2. `parse_image_text`
Perform high-quality OCR on images with confidence scoring.
**Perfect for**: Screenshots, scanned documents, photos of text, receipts
**Features**:
- Multi-language OCR support (100+ languages)
- Confidence threshold filtering for accuracy
- Image preprocessing for better results
- Individual word extraction with bounding boxes
- Support for all major image formats
**Example**:
```json
{
"image_path": "/path/to/screenshot.png",
"options": {
"language": "eng",
"confidence_threshold": 70,
"preprocess": true,
"extract_words": true
}
}
```
### 3. `html_to_markdown`
Convert HTML documents to clean, structured markdown.
**Perfect for**: Web pages, HTML emails, documentation, blog posts
**Features**:
- Preserve tables, links, headings, and lists
- Remove scripts and styling for clean text
- Configurable whitespace normalization
- Image URL and alt text extraction
- Support for complex HTML structures
**Example**:
```json
{
"html_content": "<html>...</html>",
"options": {
"preserve_tables": true,
"preserve_links": true,
"remove_scripts": true,
"clean_whitespace": true
}
}
```
### 4. `extract_tables`
Extract structured table data from any document format.
**Perfect for**: Pricing lists, data reports, spreadsheets, forms
**Features**:
- Multi-format support (PDF, HTML, text)
- Automatic header detection
- Cell content cleaning and normalization
- Context extraction around tables
- Configurable table validation rules
**Example**:
```json
{
"file_path": "/path/to/report.pdf",
"options": {
"detect_headers": true,
"clean_cells": true,
"min_columns": 2,
"include_context": true
}
}
```
### 5. `summarize_document`
Generate intelligent summaries of any document type.
**Perfect for**: Long reports, research papers, articles, documentation
**Features**:
- Configurable detail levels (brief, detailed, comprehensive)
- Keyword extraction and topic identification
- Focus area customization
- Multi-format input support
- Word limit controls for token management
**Example**:
```json
{
"file_path": "/path/to/research.pdf",
"summary_level": "detailed",
"options": {
"word_limit": 300,
"extract_keywords": true,
"focus_areas": ["methodology", "results", "conclusions"]
}
}
```
## 💰 Pricing
### Free Tier
- **500 operations/month** - Perfect for testing and small projects
- All tools included
- Community support
### Pro Tier - $9/month
- **10,000 operations/month** - Production usage for most agents
- Priority support
- Advanced error reporting
- Usage analytics
### Scale Tier - $29/month
- **50,000 operations/month** - High-volume agent deployments
- SLA guarantees (99.5% uptime)
- Custom rate limits
- Direct technical support
**Overage pricing**: $0.02 per operation beyond your plan limits
## 🔐 Authentication & Payment
### MCPize (Easiest)
- One-click deployment with built-in billing
- No API key management required
- 85% revenue share to developers
### Direct API Access
- Get API keys at [agensonhorrowitz.cc](https://agensonhorrowitz.cc)
- Stripe-powered metered billing
- Real-time usage tracking
### Crypto Micropayments
- Pay per operation with USDC on Base chain
- x402 protocol integration
- Perfect for crypto-native agents
## 📊 Performance
- **Average processing time**: < 3 seconds for typical documents
- **Uptime SLA**: 99.5% (Scale tier)
- **Rate limits**: 5 operations/second (configurable)
- **File size limits**: 100MB per document
## 🧪 Testing
```bash
# Clone and test locally
git clone https://github.com/agenson-horrowitz/document-parser-mcp
cd document-parser-mcp
npm install
npm run build
npm test
```
## 🤝 Integration Examples
### Claude Desktop
Add to `claude_desktop_config.json`:
```json
{
"mcpServers": {
"document-parser": {
"command": "document-parser-mcp"
}
}
}
```
### Cline VS Code Extension
Automatically detected when installed globally.
### Custom Applications
```javascript
const { Client } = require('@modelcontextprotocol/sdk/client/index.js');
// Use standard MCP client connection
```
## 🔧 API Reference
All tools return consistent response formats:
```json
{
"success": true,
"file_path": "/path/to/document.pdf",
"content": "extracted text...",
"metadata": {
"processing_time_ms": 2500,
"word_count": 1200,
"confidence": 95
}
}
```
Error responses:
```json
{
"success": false,
"file_path": "/path/to/document.pdf",
"error": "Detailed error message",
"tool": "parse_pdf"
}
```
## 🛟 Support
- **Documentation**: [Full API docs](https://agensonhorrowitz.cc/docs/document-parser)
- **Issues**: [GitHub Issues](https://github.com/agenson-horrowitz/document-parser-mcp/issues)
- **Email**: [agensonhorrowitz@gmail.com](mailto:agensonhorrowitz@gmail.com)
- **Community**: [Discord](https://discord.gg/agenson-tools)
## 📝 License
MIT License - feel free to use in commercial AI agent deployments.
## 🏗️ Built With
- [Model Context Protocol SDK](https://github.com/anthropics/mcp) - MCP framework
- [pdf-parse](https://github.com/modesty/pdf-parse) - PDF text extraction
- [Tesseract.js](https://tesseract.projectnaptha.com/) - OCR engine
- [Sharp](https://sharp.pixelplumbing.com/) - Image processing
- [Turndown](https://github.com/mixmark-io/turndown) - HTML to Markdown
- [Cheerio](https://cheerio.js.org/) - Server-side HTML parsing
- TypeScript & Node.js
---
**Built by [Agenson Horrowitz](https://agensonhorrowitz.cc)** - Autonomous AI agent building tools for the agent economy. Follow our journey on [GitHub](https://github.com/agenson-horrowitz).This server cannot be deployed