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techtenstein pdf mcp

techtenstein pdf mcp

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@sathvic-kolluPythonUpdated 1mo ago

PDF text and table extraction plus metadata. Supports OCR for scanned documents.

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Techtenstein PDF MCP

MCP server that gives your Claude, Cline, or Cursor session the ability to extract text, tables, and metadata from any PDF URL — including scanned PDFs via OCR. Powered by the Techtenstein PDF Extract API.

Tools exposed

  • pdf_extract_text(pdf_url, ocr=False) — Extract all text from a PDF as clean plain text
  • pdf_extract_tables(pdf_url) — Extract all tables as structured row arrays
  • pdf_metadata(pdf_url) — Get title, author, page count, creation date, encryption status

Install (Claude Desktop)

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "techtenstein-pdf": {
      "command": "uvx",
      "args": ["techtenstein-pdf-mcp"],
      "env": {
        "TECHTENSTEIN_API_KEY": "your_key_from_techtenstein.com"
      }
    }
  }
}

Restart Claude Desktop. pdf_extract_text, pdf_extract_tables, and pdf_metadata will appear as available tools.

Install (Cline / VS Code)

Cline auto-detects MCP servers from your Claude Desktop config. Same setup as above works.

Install (Cursor)

Add to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "techtenstein-pdf": {
      "command": "uvx",
      "args": ["techtenstein-pdf-mcp"],
      "env": {"TECHTENSTEIN_API_KEY": "your_key"}
    }
  }
}

Get an API key

Free tier (50 extractions/day, no card): https://apis.techtenstein.com

Paid tiers start at $5/month for 2,000 extractions.

Example usage

Once installed, ask Claude:

"Extract the tables from this earnings report PDF: https://example.com/q4.pdf"

Claude will call pdf_extract_tables and return a clean structured view of every table on the page.

Or for scanned documents:

"This PDF is a scanned invoice. Extract the text: https://example.com/invoice.pdf"

Claude will call pdf_extract_text(pdf_url, ocr=True) and read the image-based text via OCR.

Response schema (text mode)

{
  "text": "Full extracted body text...",
  "page_count": 12,
  "word_count": 3450,
  "ms": 240
}

Response schema (tables mode)

{
  "tables": [
    {
      "page": 3,
      "rows": [
        ["Product", "Q1", "Q2", "Q3", "Q4"],
        ["Widget A", "1200", "1350", "1420", "1600"]
      ]
    }
  ]
}

Support

License

MIT