- Bypass all complex processing in summary_only mode
- Extract only first 50 paragraphs, max 10 headings, 5 content paragraphs
- Add bookmark detection for chapter navigation hints
- Limit summary content to 2000 chars max
- Prevent 1,282,370 token responses with surgical precision
- Show bookmark names as chapter start indicators
- Extract headings with page numbers during document processing
- Generate optimized page ranges for each section/chapter
- Provide intelligent chunking suggestions (15-page optimal chunks)
- Classify section types (chapter, section, subsection, etc.)
- Calculate actual section lengths based on heading positions
- Include suggested_chunking with ready-to-use page ranges
- Perfect for extracting 200+ page documents section by section
- Analyze document size and complexity before processing
- Provide clear workflow recommendations in response metadata
- Strongly recommend summary_only + page_range for large documents (>10 pages)
- Add warning system for suboptimal usage patterns
- Update parameter descriptions with best practice guidance
- Help users avoid 25k token response limits proactively
- Add page break detection using Word XML structure
- Process only specified pages instead of full document + truncation
- Route page-range requests to python-docx for granular control
- Skip mammoth for page-specific processing (mammoth processes full doc)
- Add page metadata to results when filtering is used
- Significantly reduce memory usage and response size for large documents
- Comprehensive Microsoft Office document processing server
- Support for Word (.docx, .doc), Excel (.xlsx, .xls), PowerPoint (.pptx, .ppt), CSV
- 6 universal tools: extract_text, extract_images, extract_metadata, detect_office_format, analyze_document_health, get_supported_formats
- Multi-library fallback system for robust processing
- URL support with intelligent caching
- Legacy Office format support (97-2003)
- FastMCP integration with async architecture
- Production ready with comprehensive documentation
🤖 Generated with Claude Code (claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>