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Related Servers

Alternatives to pdfmux

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    Related Servers

    • A
      license
      Not graded
      quality
      A
      maintenance
      Extracts text and tables from PDFs for AI agents via MCP, enabling structured data retrieval from invoices, reports, and statements.
      78 PyPI
      1
      MIT
    • F
      license
      Not graded
      quality
      C
      maintenance
      Enables AI agents to extract structured data from PDFs with confidence scores and provenance, and to search, review, and correct documents via MCP tools, resources, and prompts.
      -
    • A
      license
      A
      quality
      A
      maintenance
      Enables Claude and other MCP-compatible agents to process documents, extract structured data, detect PII, and export LLM-ready datasets through natural language tool calls.
      8
      63 PyPI
      1
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI-powered extraction and analysis of PDF documents with 40+ specialized tools for text, tables, images, layout analysis, security assessment, and document intelligence. Supports both text-based and scanned PDFs with OCR capabilities.
      308 PyPI
      10
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      MCP server that extracts clean text, tables, and structured data from documents, images, code, and audio files, supporting 97 formats with OCR, transcription, and code intelligence.
      MIT

    TDQS

    A3.7/5.0

    Scored across 7 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: metadata extraction, full conversion, quality analysis, batch processing, structured data extraction, streaming extraction, and verification. No two tools overlap in functionality, and descriptions guide selection.

    Naming Consistency4/5

    Tool names mostly follow a verb_noun pattern (e.g., get_pdf_metadata, convert_pdf), but batch_convert reverses the order and extract_structured/extract_streaming use adjective noun after verb. This minor inconsistency lowers the score slightly.

    Tool Count5/5

    Seven tools cover the core PDF extraction workflow—metadata, analysis, conversion, batch, structured extraction, streaming, and verification—without redundancy. The scope is well-balanced for the domain.

    Completeness4/5

    The tool set covers the main PDF processing tasks (metadata, conversion, analysis, extraction, streaming, verification) but lacks basic operations like merging or splitting. For an extraction-focused server, the coverage is very good.

    Maintenance

    ActivityMaintained
    ResponsivenessUnresponsive