+Development Installation
```bash
-# 1๏ธโฃ Clone and install
git clone https://github.com/rsp2k/mcp-pdf
cd mcp-pdf
uv sync
-# 2๏ธโฃ Install system dependencies (Ubuntu/Debian)
+# System dependencies (Ubuntu/Debian)
sudo apt-get install tesseract-ocr tesseract-ocr-eng poppler-utils ghostscript
-# 3๏ธโฃ Verify installation
-uv run python examples/verify_installation.py
-
-# 4๏ธโฃ Run the MCP server
-uv run mcp-pdf
-```
-
-
-๐ง Claude Desktop Integration (click to expand)
-
-### **๐ฆ Production Installation (PyPI)**
-
-```bash
-# For personal use across all projects
-claude mcp add -s local pdf-tools uvx mcp-pdf
-
-# For project-specific use (isolated)
-claude mcp add -s project pdf-tools uvx mcp-pdf
-```
-
-### **๐ ๏ธ Development Installation (Source)**
-
-```bash
-# For local development from source
-claude mcp add -s project pdf-tools-dev uv -- --directory /path/to/mcp-pdf run mcp-pdf
-```
-
-### **โ๏ธ Manual Configuration**
-Add to your `claude_desktop_config.json`:
-```json
-{
- "mcpServers": {
- "pdf-tools": {
- "command": "uvx",
- "args": ["mcp-pdf"]
- }
- }
-}
-```
-*Restart Claude Desktop and unlock PDF intelligence!*
-
-
-
----
-
-## ๐ญ **See AI-Powered Intelligence In Action**
-
-### **๐ Business Intelligence Workflow**
-```python
-# Complete financial report analysis in seconds
-health = await analyze_pdf_health("quarterly-report.pdf")
-classification = await classify_content("quarterly-report.pdf")
-summary = await summarize_content("quarterly-report.pdf", summary_length="medium")
-
-# Smart table extraction - prevents token overflow on large tables
-tables = await extract_tables("quarterly-report.pdf", pages="5-7", max_rows_per_table=100)
-# Or get just table structure without data
-table_summary = await extract_tables("quarterly-report.pdf", pages="5-7", summary_only=True)
-
-charts = await extract_charts("quarterly-report.pdf")
-
-# Get instant insights
-{
- "document_type": "Financial Report",
- "health_score": 9.2,
- "key_insights": [
- "Revenue increased 23% YoY",
- "Operating margin improved to 15.3%",
- "Strong cash flow generation"
- ],
- "tables_extracted": 12,
- "charts_found": 8,
- "processing_time": 2.1
-}
-```
-
-### **๐ Document Security Assessment**
-```python
-# Comprehensive security analysis
-security = await analyze_pdf_security("sensitive-document.pdf")
-watermarks = await detect_watermarks("sensitive-document.pdf")
-health = await analyze_pdf_health("sensitive-document.pdf")
-
-# Enterprise-grade security insights
-{
- "encryption_type": "AES-256",
- "permissions": {
- "print": false,
- "copy": false,
- "modify": false
- },
- "security_warnings": [],
- "watermarks_detected": true,
- "compliance_ready": true
-}
-```
-
-### **๐ Academic Research Processing**
-```python
-# Advanced research paper analysis
-layout = await analyze_layout("research-paper.pdf", pages=[1,2,3])
-summary = await summarize_content("research-paper.pdf", summary_length="long")
-citations = await extract_text("research-paper.pdf", pages=[15,16,17])
-
-# Research intelligence delivered
-{
- "reading_complexity": "Graduate Level",
- "main_topics": ["Machine Learning", "Natural Language Processing"],
- "citation_count": 127,
- "figures_detected": 15,
- "methodology_extracted": true
-}
-```
-
----
-
-## ๐ ๏ธ **Complete Arsenal: 41 Specialized Tools**
-
-
-
-### **๐ฏ Document Intelligence & Analysis**
-
-| ๐ง **Tool** | ๐ **Purpose** | โก **AI Powered** | ๐ฏ **Accuracy** |
-|-------------|---------------|-----------------|----------------|
-| `classify_content` | AI-powered document type detection | โ
Yes | 97% |
-| `summarize_content` | Intelligent key insights extraction | โ
Yes | 95% |
-| `analyze_pdf_health` | Comprehensive quality assessment | โ
Yes | 99% |
-| `analyze_pdf_security` | Security & vulnerability analysis | โ
Yes | 99% |
-| `compare_pdfs` | Advanced document comparison | โ
Yes | 96% |
-
-### **๐ Core Content Extraction**
-
-| ๐ง **Tool** | ๐ **Purpose** | โก **Speed** | ๐ฏ **Accuracy** |
-|-------------|---------------|-------------|----------------|
-| `extract_text` | Multi-method text extraction with auto-chunking | **Ultra Fast** | 99.9% |
-| `extract_tables` | Smart table extraction with token overflow protection | **Fast** | 98% |
-| `ocr_pdf` | Advanced OCR for scanned docs | **Moderate** | 95% |
-| `extract_images` | Media extraction & processing | **Fast** | 99% |
-| `pdf_to_markdown` | Structure-preserving conversion | **Fast** | 97% |
-
-### **๐ Visual & Layout Analysis**
-
-| ๐จ **Tool** | ๐ **Purpose** | ๐ **Precision** | ๐ช **Features** |
-|-------------|---------------|-----------------|----------------|
-| `analyze_layout` | Page structure & column detection | **High** | Advanced |
-| `extract_charts` | Visual element extraction | **High** | Smart |
-| `detect_watermarks` | Watermark identification | **Perfect** | Complete |
-| `extract_vector_graphics` | PDF to SVG for schematics & drawings | **Perfect** | Multi-mode |
-
-
-
----
-
-## ๐ **Document Format Intelligence Matrix**
-
-
-
-### **๐ Universal PDF Processing Capabilities**
-
-| ๐ **Document Type** | ๐ **Detection** | ๐ **Text** | ๐ **Tables** | ๐ผ๏ธ **Images** | ๐ง **Intelligence** |
-|---------------------|-----------------|------------|--------------|--------------|-------------------|
-| **Financial Reports** | โ
Perfect | โ
Perfect | โ
Perfect | โ
Perfect | ๐ง **AI-Enhanced** |
-| **Research Papers** | โ
Perfect | โ
Perfect | โ
Excellent | โ
Perfect | ๐ง **AI-Enhanced** |
-| **Legal Documents** | โ
Perfect | โ
Perfect | โ
Good | โ
Perfect | ๐ง **AI-Enhanced** |
-| **Scanned PDFs** | โ
Auto-Detect | โ
OCR | โ
OCR | โ
Perfect | ๐ง **AI-Enhanced** |
-| **Forms & Applications** | โ
Perfect | โ
Perfect | โ
Excellent | โ
Perfect | ๐ง **AI-Enhanced** |
-| **Technical Manuals** | โ
Perfect | โ
Perfect | โ
Perfect | โ
Perfect | ๐ง **AI-Enhanced** |
-
-*โ
Perfect โข ๐ง AI-Enhanced Intelligence โข ๐ Auto-Detection*
-
-
-
----
-
-## โก **Performance That Amazes**
-
-
-
-### **๐ Real-World Benchmarks**
-
-| ๐ **Document Type** | ๐ **Pages** | โฑ๏ธ **Processing Time** | ๐ **vs Competitors** | ๐ง **Intelligence Level** |
-|---------------------|-------------|----------------------|----------------------|---------------------------|
-| Financial Report | 50 pages | 2.1 seconds | **10x faster** | **AI-Powered** |
-| Research Paper | 25 pages | 1.3 seconds | **8x faster** | **Deep Analysis** |
-| Scanned Document | 100 pages | 45 seconds | **5x faster** | **OCR + AI** |
-| Complex Forms | 15 pages | 0.8 seconds | **12x faster** | **Structure Aware** |
-
-*Benchmarked on: MacBook Pro M2, 16GB RAM โข Including AI processing time*
-
-
-
----
-
-## ๐๏ธ **Intelligent Architecture**
-
-### **๐ง Multi-Library Intelligence System**
-*Never worry about PDF compatibility or failure again*
-
-```mermaid
-graph TD
- A[PDF Input] --> B{Smart Detection}
- B --> C{Document Type}
- C -->|Text-based| D[PyMuPDF Fast Path]
- C -->|Scanned| E[OCR Processing]
- C -->|Complex Layout| F[pdfplumber Analysis]
- C -->|Tables Heavy| G[Camelot + Tabula]
-
- D -->|Success| H[โ
Content Extracted]
- D -->|Fail| I[pdfplumber Fallback]
- I -->|Fail| J[pypdf Fallback]
-
- E --> K[Tesseract OCR]
- K --> L[AI Content Analysis]
-
- F --> M[Layout Intelligence]
- G --> N[Table Intelligence]
-
- H --> O[๐ง AI Enhancement]
- L --> O
- M --> O
- N --> O
-
- O --> P[๐ฏ Structured Intelligence]
-```
-
-### **๐ฏ Intelligent Processing Pipeline**
-
-1. **๐ Smart Detection**: Automatically identify document type and optimal processing strategy
-2. **โก Optimized Extraction**: Use the fastest, most accurate method for each document
-3. **๐ก๏ธ Fallback Protection**: Seamless method switching if primary approach fails
-4. **๐ง AI Enhancement**: Apply document intelligence and content analysis
-5. **๐งน Clean Output**: Deliver perfectly structured, AI-ready intelligence
-
----
-
-## ๐ **Real-World Success Stories**
-
-
-
-### **๐ข Proven at Enterprise Scale**
-
-
-
-
-
-|
-
-### **๐ Financial Services Giant**
-*Processing 50,000+ reports monthly*
-
-**Challenge**: Analyze quarterly reports from 2,000+ companies
-
-**Results**:
-- โก **98% time reduction** (2 weeks โ 4 hours)
-- ๐ฏ **99.9% accuracy** in financial data extraction
-- ๐ฐ **$5M annual savings** in analyst time
-- ๐ **SEC compliance** maintained
-
- |
-
-
-### **๐ฅ Healthcare Research Institute**
-*Processing 100,000+ research papers*
-
-**Challenge**: Analyze medical literature for drug discovery
-
-**Results**:
-- ๐ **25x faster** literature review process
-- ๐ **95% accuracy** in data extraction
-- ๐งฌ **12 new drug targets** identified
-- ๐ **Publication in Nature** based on insights
-
- |
-
-
-|
-
-### **โ๏ธ Legal Firm Network**
-*Processing 500,000+ legal documents*
-
-**Challenge**: Document review and compliance checking
-
-**Results**:
-- ๐ **40x speed improvement** in document review
-- ๐ก๏ธ **100% security compliance** maintained
-- ๐ผ **$20M cost savings** across network
-- ๐ **Zero data breaches** during migration
-
- |
-
-
-### **๐ Global University System**
-*Processing 1M+ academic papers*
-
-**Challenge**: Create searchable academic knowledge base
-
-**Results**:
-- ๐ **50x faster** knowledge extraction
-- ๐ง **AI-ready** structured academic data
-- ๐ **97% search accuracy** improvement
-- ๐ **3 Nobel Prize** papers processed
-
- |
-
-
-
----
-
-## ๐ฏ **Advanced Features That Set Us Apart**
-
-### **๐ HTTPS URL Processing with Smart Caching**
-```python
-# Process PDFs directly from anywhere on the web
-report_url = "https://company.com/annual-report.pdf"
-analysis = await classify_content(report_url) # Downloads & caches automatically
-tables = await extract_tables(report_url) # Uses cache - instant!
-summary = await summarize_content(report_url) # Lightning fast!
-```
-
-### **๐ฉบ Comprehensive Document Health Analysis**
-```python
-# Enterprise-grade document assessment
-health = await analyze_pdf_health("critical-document.pdf")
-
-{
- "overall_health_score": 9.2,
- "corruption_detected": false,
- "optimization_potential": "23% size reduction possible",
- "security_assessment": "enterprise_ready",
- "recommendations": [
- "Document is production-ready",
- "Consider optimization for web delivery"
- ],
- "processing_confidence": 99.8
-}
-```
-
-### **๐ AI-Powered Content Classification**
-```python
-# Automatically understand document types
-classification = await classify_content("mystery-document.pdf")
-
-{
- "document_type": "Financial Report",
- "confidence": 97.3,
- "key_topics": ["Revenue", "Operating Expenses", "Cash Flow"],
- "complexity_level": "Professional",
- "suggested_tools": ["extract_tables", "extract_charts", "summarize_content"],
- "industry_vertical": "Technology"
-}
-```
-
----
-
-## ๐ค **Perfect Integration Ecosystem**
-
-### **๐ Companion to MCP Office Tools**
-*The ultimate document processing powerhouse*
-
-
-
-| ๐ง **Processing Need** | ๐ **PDF Files** | ๐ **Office Files** | ๐ **Integration** |
-|-----------------------|------------------|-------------------|-------------------|
-| **Text Extraction** | MCP PDF โ
| [MCP Office Tools](https://git.supported.systems/MCP/mcp-office-tools) โ
| **Unified API** |
-| **Table Processing** | Advanced โ
| Advanced โ
| **Cross-Format** |
-| **Image Extraction** | Smart โ
| Smart โ
| **Consistent** |
-| **Format Detection** | AI-Powered โ
| AI-Powered โ
| **Intelligent** |
-| **Health Analysis** | Complete โ
| Complete โ
| **Comprehensive** |
-
-[**๐ Get Both Tools for Complete Document Intelligence**](https://git.supported.systems/MCP/mcp-office-tools)
-
-
-
-### **๐ Unified Document Processing Workflow**
-```python
-# Process ALL document formats with unified intelligence
-pdf_analysis = await pdf_tools.classify_content("report.pdf")
-word_analysis = await office_tools.detect_office_format("report.docx")
-excel_data = await office_tools.extract_text("data.xlsx")
-
-# Cross-format document comparison
-comparison = await compare_cross_format_documents([
- pdf_analysis, word_analysis, excel_data
-])
-```
-
-### **โก Works Seamlessly With**
-- **๐ค Claude Desktop**: Native MCP protocol integration
-- **๐ Jupyter Notebooks**: Perfect for research and analysis
-- **๐ Python Applications**: Direct async/await API access
-- **๐ Web Services**: RESTful wrappers and microservices
-- **โ๏ธ Cloud Platforms**: AWS Lambda, Google Functions, Azure
-- **๐ Workflow Engines**: Zapier, Microsoft Power Automate
-
----
-
-## ๐ก๏ธ **Enterprise-Grade Security & Compliance**
-
-
-
-| ๐ **Security Feature** | โ
**Status** | ๐ **Enterprise Ready** |
-|------------------------|---------------|------------------------|
-| **Local Processing** | โ
Enabled | Documents never leave your environment |
-| **Memory Security** | โ
Optimized | Automatic sensitive data cleanup |
-| **HTTPS Validation** | โ
Enforced | Certificate validation and secure headers |
-| **Access Controls** | โ
Configurable | Role-based processing permissions |
-| **Audit Logging** | โ
Available | Complete processing audit trails |
-| **GDPR Compliant** | โ
Certified | No personal data retention |
-| **SOC2 Ready** | โ
Verified | Enterprise security standards |
-
-
-
----
-
-## ๐ **Installation & Enterprise Setup**
-
-
-๐ Quick Start (Recommended)
-
-```bash
-# Clone repository
-git clone https://github.com/rsp2k/mcp-pdf
-cd mcp-pdf
-
-# Install with uv (fastest)
-uv sync
-
-# Install system dependencies (Ubuntu/Debian)
-sudo apt-get install tesseract-ocr tesseract-ocr-eng poppler-utils ghostscript
-
-# Verify installation
-uv run python examples/verify_installation.py
-```
-
-
-
-
-๐ณ Docker Enterprise Setup
-
-```dockerfile
-FROM python:3.11-slim
-RUN apt-get update && apt-get install -y \
- tesseract-ocr tesseract-ocr-eng \
- poppler-utils ghostscript \
- default-jre-headless
-COPY . /app
-WORKDIR /app
-RUN pip install -e .
-CMD ["mcp-pdf"]
-```
-
-
-
-
-๐ Claude Desktop Integration
-
-```json
-{
- "mcpServers": {
- "pdf-tools": {
- "command": "uv",
- "args": ["run", "mcp-pdf"],
- "cwd": "/path/to/mcp-pdf"
- },
- "office-tools": {
- "command": "mcp-office-tools"
- }
- }
-}
-```
-
-*Unified document processing across all formats!*
-
-
-
-
-๐ง Development Environment
-
-```bash
-# Clone and setup
-git clone https://github.com/rsp2k/mcp-pdf
-cd mcp-pdf
-uv sync --dev
-
-# Quality checks
-uv run pytest --cov=mcp_pdf_tools
-uv run black src/ tests/ examples/
-uv run ruff check src/ tests/ examples/
-uv run mypy src/
-
-# Run all 23 tools demo
+# Verify
uv run python examples/verify_installation.py
```
@@ -564,125 +63,162 @@ uv run python examples/verify_installation.py
---
-## ๐ **What's Coming Next?**
+## Tools
-
+### Content Extraction
-### **๐ฎ Innovation Roadmap 2024-2025**
+| Tool | What it does |
+|------|-------------|
+| `extract_text` | Pull text from PDF pages with automatic chunking for large files |
+| `extract_tables` | Extract tables to JSON, CSV, or Markdown |
+| `extract_images` | Extract embedded images |
+| `extract_links` | Get all hyperlinks with page filtering |
+| `pdf_to_markdown` | Convert PDF to markdown preserving structure |
+| `ocr_pdf` | OCR scanned documents using Tesseract |
+| `extract_vector_graphics` | Export vector graphics to SVG (schematics, charts, drawings) |
+
+### Document Analysis
+
+| Tool | What it does |
+|------|-------------|
+| `extract_metadata` | Get title, author, creation date, page count, etc. |
+| `get_document_structure` | Extract table of contents and bookmarks |
+| `analyze_layout` | Detect columns, headers, footers |
+| `is_scanned_pdf` | Check if PDF needs OCR |
+| `compare_pdfs` | Diff two PDFs by text, structure, or metadata |
+| `analyze_pdf_health` | Check for corruption, optimization opportunities |
+| `analyze_pdf_security` | Report encryption, permissions, signatures |
+
+### Forms
+
+| Tool | What it does |
+|------|-------------|
+| `extract_form_data` | Get form field names and values |
+| `fill_form_pdf` | Fill form fields from JSON |
+| `create_form_pdf` | Create new forms with text fields, checkboxes, dropdowns |
+| `add_form_fields` | Add fields to existing PDFs |
+
+### Document Assembly
+
+| Tool | What it does |
+|------|-------------|
+| `merge_pdfs` | Combine multiple PDFs with bookmark preservation |
+| `split_pdf_by_pages` | Split by page ranges |
+| `split_pdf_by_bookmarks` | Split at chapter/section boundaries |
+| `reorder_pdf_pages` | Rearrange pages in custom order |
+
+### Annotations
+
+| Tool | What it does |
+|------|-------------|
+| `add_sticky_notes` | Add comment annotations |
+| `add_highlights` | Highlight text regions |
+| `add_stamps` | Add Approved/Draft/Confidential stamps |
+| `extract_all_annotations` | Export annotations to JSON |
+
+---
+
+## How Fallbacks Work
+
+The server tries multiple libraries for each operation:
+
+**Text extraction:**
+1. PyMuPDF (fastest)
+2. pdfplumber (better for complex layouts)
+3. pypdf (most compatible)
+
+**Table extraction:**
+1. Camelot (best accuracy, requires Ghostscript)
+2. pdfplumber (no dependencies)
+3. Tabula (requires Java)
+
+If a PDF fails with one library, the next is tried automatically.
+
+---
+
+## Token Management
+
+Large PDFs can overflow MCP response limits. The server handles this:
+
+- **Automatic chunking** splits large documents into page groups
+- **Table row limits** prevent huge tables from blowing up responses
+- **Summary mode** returns structure without full content
+
+```python
+# Get first 10 pages
+result = await extract_text("huge.pdf", pages="1-10")
+
+# Limit table rows
+tables = await extract_tables("data.pdf", max_rows_per_table=50)
+
+# Structure only
+tables = await extract_tables("data.pdf", summary_only=True)
+```
+
+---
+
+## URL Processing
+
+PDFs can be fetched directly from HTTPS URLs:
+
+```python
+result = await extract_text("https://example.com/report.pdf")
+```
+
+Files are cached locally for subsequent operations.
+
+---
+
+## System Dependencies
+
+Some features require system packages:
+
+| Feature | Dependency |
+|---------|-----------|
+| OCR | `tesseract-ocr` |
+| Camelot tables | `ghostscript` |
+| Tabula tables | `default-jre-headless` |
+| PDF to images | `poppler-utils` |
+
+Ubuntu/Debian:
+```bash
+sudo apt-get install tesseract-ocr tesseract-ocr-eng poppler-utils ghostscript default-jre-headless
+```
+
+---
+
+## Configuration
+
+Optional environment variables:
+
+| Variable | Purpose |
+|----------|---------|
+| `MCP_PDF_ALLOWED_PATHS` | Colon-separated directories for file output |
+| `PDF_TEMP_DIR` | Temp directory for processing (default: `/tmp/mcp-pdf-processing`) |
+| `TESSDATA_PREFIX` | Tesseract language data location |
+
+---
+
+## Development
+
+```bash
+# Run tests
+uv run pytest
+
+# With coverage
+uv run pytest --cov=mcp_pdf
+
+# Format
+uv run black src/ tests/
+
+# Lint
+uv run ruff check src/ tests/
+```
+
+---
+
+## License
+
+MIT
-
-| ๐๏ธ **Timeline** | ๐ฏ **Feature** | ๐ **Impact** |
-|-----------------|---------------|--------------|
-| **Q4 2024** | **Enhanced AI Analysis** | GPT-powered content understanding |
-| **Q1 2025** | **Batch Processing** | Process 1000+ documents simultaneously |
-| **Q2 2025** | **Cloud Integration** | Direct S3, GCS, Azure Blob support |
-| **Q3 2025** | **Real-time Streaming** | Process documents as they're created |
-| **Q4 2025** | **Multi-language OCR** | 50+ language support with AI translation |
-| **2026** | **Blockchain Verification** | Cryptographic document integrity |
-
----
-
-## ๐ญ **Complete Tool Showcase**
-
-
-๐ Business Intelligence Tools (click to expand)
-
-### **Core Extraction**
-- `extract_text` - Multi-method text extraction with layout preservation
-- `extract_tables` - Intelligent table extraction (JSON, CSV, Markdown)
-- `extract_images` - Image extraction with size filtering and format options
-- `pdf_to_markdown` - Clean markdown conversion with structure preservation
-
-### **AI-Powered Analysis**
-- `classify_content` - AI document type classification and analysis
-- `summarize_content` - Intelligent summarization with key insights
-- `analyze_pdf_health` - Comprehensive quality assessment
-- `analyze_pdf_security` - Security feature analysis and vulnerability detection
-
-
-
-
-๐ Advanced Analysis Tools (click to expand)
-
-### **Document Intelligence**
-- `compare_pdfs` - Advanced document comparison (text, structure, metadata)
-- `is_scanned_pdf` - Smart detection of scanned vs. text-based documents
-- `get_document_structure` - Document outline and structural analysis
-- `extract_metadata` - Comprehensive metadata and statistics extraction
-
-### **Visual Processing**
-- `analyze_layout` - Page layout analysis with column and spacing detection
-- `extract_charts` - Chart, diagram, and visual element extraction
-- `detect_watermarks` - Watermark detection and analysis
-- `extract_vector_graphics` - Extract vector graphics to SVG (schematics, charts, technical drawings)
-
-
-
-
-๐จ Document Manipulation Tools (click to expand)
-
-### **Content Operations**
-- `extract_form_data` - Interactive PDF form data extraction
-- `split_pdf` - Intelligent document splitting at specified pages
-- `merge_pdfs` - Multi-document merging with page range tracking
-- `rotate_pages` - Precise page rotation (90ยฐ/180ยฐ/270ยฐ)
-
-### **Optimization & Repair**
-- `convert_to_images` - PDF to image conversion with quality control
-- `optimize_pdf` - Multi-level file size optimization
-- `repair_pdf` - Automated corruption repair and recovery
-- `ocr_pdf` - Advanced OCR with preprocessing for scanned documents
-
-
-
----
-
-## ๐ **Enterprise Support & Community**
-
-
-
-### **๐ Join the PDF Intelligence Revolution!**
-
-[](https://github.com/rsp2k/mcp-pdf)
-[](https://github.com/rsp2k/mcp-pdf/issues)
-[](https://git.supported.systems/MCP/mcp-office-tools)
-
-**๐ฌ Enterprise Support Available** โข **๐ Bug Bounty Program** โข **๐ก Feature Requests Welcome**
-
-
-
-### **๐ข Enterprise Services**
-- **๐ Priority Support**: 24/7 enterprise support available
-- **๐ Training Programs**: Comprehensive team training
-- **๐ง Custom Integration**: Tailored enterprise deployments
-- **๐ Analytics Dashboard**: Usage analytics and insights
-- **๐ก๏ธ Security Audits**: Comprehensive security assessments
-
----
-
-
-
-## ๐ **License & Ecosystem**
-
-**MIT License** - Freedom to innovate everywhere
-
-**๐ค Part of the MCP Document Processing Ecosystem**
-
-*Powered by [FastMCP](https://github.com/jlowin/fastmcp) โข [Model Context Protocol](https://modelcontextprotocol.io) โข Enterprise Python*
-
-### **๐ Complete Document Processing Solution**
-
-**PDF Intelligence** โ **[MCP PDF](https://github.com/rsp2k/mcp-pdf)** (You are here!)
-**Office Intelligence** โ **[MCP Office Tools](https://git.supported.systems/MCP/mcp-office-tools)**
-**Unified Power** โ **Both Tools Together**
-
----
-
-### **โญ Star both repositories for the complete solution! โญ**
-
-**๐ [Star MCP PDF](https://github.com/rsp2k/mcp-pdf)** โข **๐ [Star MCP Office Tools](https://git.supported.systems/MCP/mcp-office-tools)**
-
-*Building the future of intelligent document processing* ๐
-
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-**๐ The Ultimate PDF Processing Intelligence Platform for AI**
+**A FastMCP server for PDF processing**
-*Transform any PDF into structured, actionable intelligence with 41 specialized tools*
+*41 tools for text extraction, OCR, tables, forms, annotations, and more*
[](https://www.python.org/downloads/)
[](https://github.com/jlowin/fastmcp)
[](https://opensource.org/licenses/MIT)
-[](https://github.com/rsp2k/mcp-pdf)
-[](https://modelcontextprotocol.io)
+[](https://pypi.org/project/mcp-pdf/)
-**๐ค Perfect Companion to [MCP Office Tools](https://git.supported.systems/MCP/mcp-office-tools)**
+**Works great with [MCP Office Tools](https://git.supported.systems/MCP/mcp-office-tools)**
---
-## โจ **What Makes MCP PDF Revolutionary?**
+## What It Does
-> ๐ฏ **The Problem**: PDFs contain incredible intelligence, but extracting it reliably is complex, slow, and often fails.
->
-> โก **The Solution**: MCP PDF delivers **AI-powered document intelligence** with **41 specialized tools** that understand both content and structure.
+MCP PDF extracts content from PDFs using multiple libraries with automatic fallbacks. If one method fails, it tries another.
-