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

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🎯 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:

# 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

# 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:

# 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

# 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

# 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

# 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

# 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

# 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

# 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

[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

[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

# 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

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🎯 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.