document-intelligence-mcp 0.1.0

MCP Server for local document analysis: PDF text extraction, table detection, DOCX parsing, language detection and keyword search — no cloud API required

document-intelligence-mcp

Local document intelligence for AI agents — extract text, detect tables, read metadata, analyze structure, search keywords, and detect language from PDF and DOCX files. No cloud API required, no API key needed.

Features

• 10 MCP Tools for PDF and DOCX processing
• Local processing — no data leaves your machine
• No API key required
• Supports PDF (via PyMuPDF + pdfplumber) and Microsoft Word DOCX (via python-docx)
• Language detection via langdetect (55+ languages)

Tools

Tool	Description
tool_extract_text_from_pdf	Extract all text from a PDF, page by page
tool_extract_tables_from_pdf	Detect and extract tables from PDF
tool_get_pdf_metadata	Read PDF metadata: title, author, dates, outline
tool_analyze_document_structure	Detect headings, font sizes, section structure
tool_search_in_pdf	Search for keywords with context in PDF
tool_extract_text_from_docx	Extract all text from a Word DOCX file
tool_extract_tables_from_docx	Extract all tables from a DOCX file
tool_analyze_docx_structure	Analyze headings, styles, and structure of DOCX
tool_count_words_and_stats	Word count, sentence count, reading time, top words
tool_detect_document_language	Detect language of PDF or DOCX (55+ languages)

Installation

pip install document-intelligence-mcp

Claude Desktop Configuration

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "document-intelligence": {
      "command": "document-intelligence-mcp"
    }
  }
}

Usage Examples

Extract text from a PDF:

Extract the text from /path/to/report.pdf

Find tables in a PDF:

Find all tables in /path/to/financial_report.pdf

Search for a keyword:

Search for "revenue" in /path/to/annual_report.pdf

Get document stats:

Count the words and estimate reading time for /path/to/document.docx

Detect language:

What language is /path/to/document.pdf written in?

Requirements

• Python 3.10+
• PyMuPDF >= 1.24.0
• pdfplumber >= 0.11.0
• python-docx >= 1.1.0
• langdetect >= 1.0.9

License

MIT License — free to use, modify, and distribute.

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