mcp-pdf-tools/MCP_DOCX_TOOLS_PLAN.md

# MCP Office Tools - Comprehensive Planning Document

*A companion server for Microsoft Office document processing to complement MCP PDF Tools*

---

## 🎯 Project Vision

Create a comprehensive **Microsoft Office document processing server** that matches the quality and scope of MCP PDF Tools, providing 25+ specialized tools for **all Microsoft Office formats** including:

- **Word Documents**: `.docx`, `.doc`, `.docm`, `.dotx`, `.dot`
- **Excel Spreadsheets**: `.xlsx`, `.xls`, `.xlsm`, `.xltx`, `.xlt`, `.csv`
- **PowerPoint Presentations**: `.pptx`, `.ppt`, `.pptm`, `.potx`, `.pot`
- **Legacy Formats**: Full support for Office 97-2003 formats
- **Template Files**: Document, spreadsheet, and presentation templates

## 📊 Architecture Overview

### **Core Libraries by Format**

**Word Documents (.docx, .doc, .docm)**
- **`python-docx`**: Modern DOCX manipulation and reading
- **`python-docx2`**: Enhanced DOCX features and complex documents
- **`olefile`**: Legacy .doc format processing (OLE compound documents)
- **`msoffcrypto-tool`**: Encrypted/password-protected files
- **`mammoth`**: High-quality HTML/Markdown conversion
- **`docx2txt`**: Fallback text extraction for damaged files

**Excel Spreadsheets (.xlsx, .xls, .xlsm)**
- **`openpyxl`**: Modern Excel file manipulation (.xlsx, .xlsm)
- **`xlrd`**: Legacy Excel file reading (.xls)
- **`xlwt`**: Legacy Excel file writing (.xls)
- **`pandas`**: Data analysis and CSV processing
- **`xlsxwriter`**: High-performance Excel file creation

**PowerPoint Presentations (.pptx, .ppt, .pptm)**
- **`python-pptx`**: Modern PowerPoint manipulation
- **`pyodp`**: OpenDocument presentation support
- **`olefile`**: Legacy .ppt format processing

**Universal Libraries**
- **`lxml`**: Advanced XML processing for Office Open XML
- **`Pillow`**: Image extraction and processing
- **`beautifulsoup4`**: HTML processing for conversions
- **`chardet`**: Character encoding detection for legacy files

### **Project Structure**
```
mcp-office-tools/
├── src/
│   └── mcp_office_tools/
│       ├── __init__.py
│       ├── server.py              # Main FastMCP server
│       ├── word/                  # Word document processing
│       │   ├── extractors.py      # Text, tables, images, metadata
│       │   ├── analyzers.py       # Content analysis, classification
│       │   └── converters.py      # Format conversion
│       ├── excel/                 # Excel spreadsheet processing
│       │   ├── extractors.py      # Data, charts, formulas
│       │   ├── analyzers.py       # Data analysis, validation
│       │   └── converters.py      # CSV, JSON, HTML export
│       ├── powerpoint/            # PowerPoint presentation processing
│       │   ├── extractors.py      # Text, images, slide content
│       │   ├── analyzers.py       # Presentation analysis
│       │   └── converters.py      # HTML, markdown export
│       ├── legacy/                # Legacy format handlers
│       │   ├── doc_handler.py     # .doc file processing
│       │   ├── xls_handler.py     # .xls file processing
│       │   └── ppt_handler.py     # .ppt file processing
│       └── utils/                 # Shared utilities
│           ├── file_detection.py  # Format detection
│           ├── caching.py         # URL caching
│           └── validation.py      # File validation
├── tests/
├── examples/
├── docs/
├── pyproject.toml
├── README.md
└── CLAUDE.md
```

## 🔧 Comprehensive Tool Suite (30 Tools)

### **📄 Universal Processing Tools (8 Tools)**
*Work across all Office formats with intelligent format detection*

| Tool | Description | Formats Supported | Priority |
|------|-------------|-------------------|----------|
| `extract_text` | Multi-method text extraction with formatting preservation | All Word, Excel, PowerPoint | High |
| `extract_images` | Image extraction with metadata and format options | All formats | High |
| `extract_metadata` | Document properties, statistics, and technical info | All formats | High |
| `detect_format` | Intelligent file format detection and validation | All formats | High |
| `analyze_document_health` | File integrity, corruption detection, version analysis | All formats | High |
| `compare_documents` | Cross-format document comparison and change tracking | All formats | Medium |
| `convert_to_pdf` | Universal PDF conversion (requires LibreOffice) | All formats | Medium |
| `extract_hyperlinks` | URL and internal link extraction and analysis | All formats | Medium |

### **📝 Word Document Tools (8 Tools)**
*Specialized for .docx, .doc, .docm, .dotx, .dot formats*

| Tool | Description | Legacy Support | Priority |
|------|-------------|----------------|----------|
| `word_extract_tables` | Table extraction optimized for Word documents | ✅ .doc support | High |
| `word_get_structure` | Heading hierarchy, outline, TOC, and section analysis | ✅ .doc support | High |
| `word_extract_comments` | Comments, tracked changes, and review data | ✅ .doc support | High |
| `word_extract_footnotes` | Footnotes, endnotes, and citations | ✅ .doc support | High |
| `word_to_markdown` | Clean markdown conversion with structure preservation | ✅ .doc support | High |
| `word_to_html` | HTML export with inline CSS styling | ✅ .doc support | Medium |
| `word_merge_documents` | Combine multiple Word documents with style preservation | ✅ .doc support | Medium |
| `word_split_document` | Split by sections, pages, or heading levels | ✅ .doc support | Medium |

### **📊 Excel Spreadsheet Tools (8 Tools)**
*Specialized for .xlsx, .xls, .xlsm, .xltx, .xlt, .csv formats*

| Tool | Description | Legacy Support | Priority |
|------|-------------|----------------|----------|
| `excel_extract_data` | Cell data extraction with formula evaluation | ✅ .xls support | High |
| `excel_extract_charts` | Chart and graph extraction with data | ✅ .xls support | High |
| `excel_get_sheets` | Worksheet enumeration and metadata | ✅ .xls support | High |
| `excel_extract_formulas` | Formula extraction and dependency analysis | ✅ .xls support | High |
| `excel_to_csv` | CSV export with sheet and range selection | ✅ .xls support | High |
| `excel_to_json` | JSON export with hierarchical data structure | ✅ .xls support | Medium |
| `excel_analyze_data` | Data quality, statistics, and validation | ✅ .xls support | Medium |
| `excel_merge_workbooks` | Combine multiple Excel files | ✅ .xls support | Medium |

### **🎯 PowerPoint Tools (6 Tools)**
*Specialized for .pptx, .ppt, .pptm, .potx, .pot formats*

| Tool | Description | Legacy Support | Priority |
|------|-------------|----------------|----------|
| `ppt_extract_slides` | Slide content and structure extraction | ✅ .ppt support | High |
| `ppt_extract_speaker_notes` | Speaker notes and hidden content | ✅ .ppt support | High |
| `ppt_to_html` | HTML export with slide navigation | ✅ .ppt support | High |
| `ppt_to_markdown` | Markdown conversion with slide structure | ✅ .ppt support | Medium |
| `ppt_extract_animations` | Animation and transition analysis | ✅ .ppt support | Low |
| `ppt_merge_presentations` | Combine multiple PowerPoint files | ✅ .ppt support | Medium |

## 🌟 Key Features & Innovations

### **1. Universal Format Support**
Complete Microsoft Office ecosystem coverage:
```python
# Intelligent format detection and processing
file_info = await detect_format("document.unknown")
# Returns: {"format": "doc", "version": "Office 97-2003", "encrypted": false}

if file_info["format"] in ["docx", "doc"]:
    text = await extract_text("document.unknown")  # Auto-handles format
elif file_info["format"] in ["xlsx", "xls"]:
    data = await excel_extract_data("document.unknown")
elif file_info["format"] in ["pptx", "ppt"]:
    slides = await ppt_extract_slides("document.unknown")
```

### **2. Legacy Format Excellence**
Full support for Office 97-2003 formats:
- **OLE Compound Document parsing** for .doc, .xls, .ppt
- **Character encoding detection** for international documents
- **Password-protected file handling** with msoffcrypto-tool
- **Graceful degradation** when features aren't available in legacy formats

### **3. Intelligent Multi-Library Fallbacks**
```python
# Word document processing with fallbacks
async def extract_word_text_with_fallback(file_path: str):
    try:
        return await extract_with_python_docx(file_path)    # Modern .docx
    except Exception:
        try:
            return await extract_with_mammoth(file_path)     # Better formatting
        except Exception:
            try:
                return await extract_with_olefile(file_path) # Legacy .doc
            except Exception:
                return await extract_with_docx2txt(file_path) # Last resort
```

### **4. Cross-Format Intelligence**
- **Unified metadata extraction** across all formats
- **Cross-format document comparison** (compare .docx with .doc)
- **Format conversion pipelines** (Excel → CSV → Markdown)
- **Content analysis** that works regardless of source format

### **🔧 Content Manipulation (4 Tools)**
| Tool | Description | Priority |
|------|-------------|----------|
| `merge_documents` | Combine multiple DOCX files with style preservation | High |
| `split_document` | Split by sections, pages, or heading levels | High |
| `extract_sections` | Extract specific sections or page ranges | Medium |
| `modify_styles` | Apply consistent formatting and style changes | Medium |

### **🔄 Format Conversion (4 Tools)**
| Tool | Description | Priority |
|------|-------------|----------|
| `docx_to_markdown` | Clean markdown conversion with structure preservation | High |
| `docx_to_html` | HTML export with inline CSS styling | High |
| `docx_to_txt` | Plain text extraction with layout options | Medium |
| `docx_to_pdf` | PDF conversion (requires LibreOffice/pandoc) | Low |

### **📎 Advanced Features (3 Tools)**
| Tool | Description | Priority |
|------|-------------|----------|
| `extract_hyperlinks` | URL extraction and link analysis | Medium |
| `extract_comments` | Comments, tracked changes, and review data | Medium |
| `extract_footnotes` | Footnotes, endnotes, and citations | Low |

## 🌟 Key Features & Innovations

### **1. Multi-Library Fallback System**
Similar to PDF Tools' intelligent fallback:
```python
# Text extraction with fallbacks
async def extract_text_with_fallback(docx_path: str):
    try:
        return await extract_with_python_docx(docx_path)  # Primary method
    except Exception:
        try:
            return await extract_with_mammoth(docx_path)   # Formatting-aware
        except Exception:
            return await extract_with_docx2txt(docx_path)  # Maximum compatibility
```

### **2. URL Support**
- Direct processing of DOCX files from HTTPS URLs
- Intelligent caching (1-hour cache like PDF Tools)
- Content validation and security headers
- Support for cloud storage links (OneDrive, Google Drive, etc.)

### **3. Smart Document Detection**
- Automatic detection of document types
- Template identification
- Style analysis and recommendations
- Corruption detection and repair suggestions

### **4. Modern Async Architecture**
- Full async/await implementation
- Concurrent processing capabilities
- Resource management and cleanup
- Performance monitoring and timing

## 📊 Real-World Use Cases

### **📈 Business Intelligence & Reporting**
```python
# Comprehensive quarterly report analysis (Word + Excel + PowerPoint)
word_summary = await extract_text("quarterly-report.docx")
excel_data = await excel_extract_data("financial-data.xlsx", sheets=["Revenue", "Expenses"])
ppt_insights = await ppt_extract_slides("presentation.pptx")

# Cross-format analysis
tables = await word_extract_tables("quarterly-report.docx")
charts = await excel_extract_charts("financial-data.xlsx")
metadata = await extract_metadata("quarterly-report.doc")  # Legacy support
```

### **📚 Academic Research & Paper Processing**
```python
# Multi-format research workflow
paper_structure = await word_get_structure("research-paper.docx")
data_analysis = await excel_analyze_data("research-data.xls")  # Legacy Excel
citations = await word_extract_footnotes("research-paper.docx")

# Legacy format support
old_paper = await extract_text("archive-paper.doc")  # Office 97-2003
old_data = await excel_extract_data("legacy-dataset.xls")
```

### **🏢 Corporate Document Management**
```python
# Legacy document migration and modernization
legacy_docs = ["policy.doc", "procedures.xls", "training.ppt"]
for doc in legacy_docs:
    format_info = await detect_format(doc)
    health = await analyze_document_health(doc)
    
    if format_info["format"] == "doc":
        modern_content = await word_to_markdown(doc)
    elif format_info["format"] == "xls":
        csv_data = await excel_to_csv(doc)
    elif format_info["format"] == "ppt":
        html_slides = await ppt_to_html(doc)
```

### **📋 Data Analysis & Business Intelligence**
```python
# Excel-focused data processing
workbook_info = await excel_get_sheets("sales-data.xlsx")
quarterly_data = await excel_extract_data("sales-data.xlsx", 
                                         sheets=["Q1", "Q2", "Q3", "Q4"])
formulas = await excel_extract_formulas("calculations.xlsm")

# Legacy Excel processing
old_data = await excel_extract_data("historical-sales.xls")  # Pre-2007 format
combined_data = await excel_merge_workbooks(["new-data.xlsx", "old-data.xls"])
```

### **🎯 Presentation Analysis & Content Extraction**
```python
# PowerPoint content extraction and analysis
slides = await ppt_extract_slides("company-presentation.pptx")
speaker_notes = await ppt_extract_speaker_notes("training-deck.pptx")
images = await extract_images("product-showcase.ppt")  # Legacy PowerPoint

# Cross-format presentation workflows
presentation_text = await extract_text("slides.pptx")
supporting_data = await excel_extract_data("presentation-data.xlsx")
documentation = await word_extract_text("presentation-notes.docx")
```

### **🔄 Format Conversion & Migration**
```python
# Universal format conversion pipelines
office_files = ["document.doc", "spreadsheet.xls", "presentation.ppt"]

for file in office_files:
    # Convert everything to modern formats and web-friendly outputs
    if file.endswith(('.doc', '.docx')):
        markdown = await word_to_markdown(file)
        html = await word_to_html(file)
    elif file.endswith(('.xls', '.xlsx')):
        csv = await excel_to_csv(file)
        json_data = await excel_to_json(file)
    elif file.endswith(('.ppt', '.pptx')):
        html_slides = await ppt_to_html(file)
        slide_markdown = await ppt_to_markdown(file)
```

## 🔧 Technical Implementation Plan

### **Phase 1: Foundation (5 Tools)**
1. `extract_text` - Multi-method text extraction
2. `extract_metadata` - Document properties and statistics
3. `get_document_structure` - Heading and outline analysis
4. `docx_to_markdown` - Clean markdown conversion
5. `analyze_document_health` - Basic integrity checking

### **Phase 2: Intelligence (6 Tools)**
1. `extract_tables` - Table extraction and conversion
2. `extract_images` - Image extraction with metadata
3. `classify_content` - Document type detection
4. `summarize_content` - Content summarization
5. `compare_documents` - Document comparison
6. `analyze_readability` - Reading level analysis

### **Phase 3: Manipulation (6 Tools)**
1. `merge_documents` - Document combination
2. `split_document` - Document splitting
3. `extract_sections` - Section extraction
4. `docx_to_html` - HTML conversion
5. `extract_hyperlinks` - Link analysis
6. `extract_comments` - Review data extraction

### **Phase 4: Advanced (5 Tools)**
1. `modify_styles` - Style manipulation
2. `analyze_formatting` - Format analysis
3. `docx_to_txt` - Text conversion
4. `extract_footnotes` - Citation extraction
5. `docx_to_pdf` - PDF conversion

## 📚 Dependencies

### **Core Libraries**
```toml
[dependencies]
python = "^3.11"
fastmcp = "^0.5.0"
python-docx = "^1.1.0"
mammoth = "^1.6.0"
docx2txt = "^0.8"
lxml = "^4.9.0"
pillow = "^10.0.0"
beautifulsoup4 = "^4.12.0"
aiohttp = "^3.9.0"
aiofiles = "^23.2.0"
```

### **Optional Libraries**
```toml
[dependencies.optional]
pypandoc = "^1.11"        # For PDF conversion
nltk = "^3.8"             # For readability analysis
spacy = "^3.7"            # For advanced NLP
textstat = "^0.7"         # For readability metrics
```

## 🧪 Testing Strategy

### **Unit Tests**
- Document parsing validation
- Text extraction accuracy
- Format conversion quality
- Error handling robustness

### **Integration Tests**
- Multi-format processing
- URL handling and caching
- Concurrent operation testing
- Performance benchmarking

### **Document Test Suite**
- Various DOCX format versions
- Complex formatting scenarios
- Corrupted file handling
- Large document processing

## 📖 Documentation Plan

### **README Structure**
Following the successful PDF Tools model:
1. **Compelling Introduction** - What we built and why
2. **Tool Categories** - Organized by functionality
3. **Real-World Examples** - Practical usage scenarios
4. **Installation Guide** - Quick start and integration
5. **API Documentation** - Complete reference
6. **Architecture Deep-Dive** - Technical implementation

### **Examples and Tutorials**
- Business document automation
- Academic paper processing
- Content migration workflows
- Document analysis pipelines

## 🚀 Success Metrics

### **Functionality Goals**
- ✅ 22 comprehensive tools covering all DOCX processing needs
- ✅ Multi-library fallback system for robust operation
- ✅ URL processing with intelligent caching
- ✅ Professional documentation with examples

### **Quality Standards**
- ✅ 100% lint-free code (ruff compliance)
- ✅ Comprehensive type hints
- ✅ Async-first architecture
- ✅ Robust error handling
- ✅ Performance optimization

### **User Experience**
- ✅ Intuitive API design
- ✅ Clear error messages
- ✅ Comprehensive examples
- ✅ Easy integration paths

## 🔗 Integration with MCP PDF Tools

### **Shared Patterns**
- Consistent API design
- Similar caching strategies
- Matching error handling
- Parallel documentation structure

### **Complementary Features**
- Cross-format conversion (DOCX ↔ PDF)
- Document comparison across formats
- Unified document analysis pipelines
- Shared utility functions

### **Combined Workflows**
```python
# Process both PDF and DOCX in same workflow
pdf_summary = await pdf_tools.summarize_content("document.pdf")
docx_summary = await docx_tools.summarize_content("document.docx")
comparison = await compare_cross_format(pdf_summary, docx_summary)
```

## 📅 Development Timeline

### **Week 1-2: Foundation**
- Project setup and core architecture
- Basic text extraction and metadata tools
- Testing framework and CI/CD

### **Week 3-4: Core Features**
- Table and image extraction
- Document structure analysis
- Format conversion basics

### **Week 5-6: Intelligence**
- Document classification and analysis
- Content summarization
- Health assessment

### **Week 7-8: Advanced Features**
- Document manipulation
- Advanced conversions
- Performance optimization

### **Week 9-10: Polish**
- Comprehensive documentation
- Example creation
- Integration testing

---

## 🎯 Next Steps

1. **Create project repository** with proper structure
2. **Set up development environment** with uv and dependencies
3. **Implement core text extraction** as foundation
4. **Build out tool categories** systematically
5. **Create comprehensive documentation** following PDF Tools model

This companion server will provide the same level of quality and comprehensiveness as MCP PDF Tools, creating a powerful document processing ecosystem for the MCP protocol.