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Alternatives to pdf-mcp

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    Related Servers

    • F
      license
      Not graded
      quality
      D
      maintenance
      A local MCP server that extracts text-layer content from PDF files, enabling AI agents to inspect, extract text, outlines, and page content.
      -
    • A
      license
      Not graded
      quality
      B
      maintenance
      MCP server that reads PDFs and exposes them as structured Markdown, metadata, outlines, images, and tables to LLM consumers via tools like pdf_read_markdown and pdf_info.
      Apache 2.0
    • A
      license
      A
      quality
      D
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      An MCP server that enables AI assistants to read, search, and analyze PDF files from local paths or URLs. It provides tools for extracting specific page ranges, searching for terms, and retrieving document metadata.
      4
      20 npm
      1
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      A local MCP server that drives PDFium and pypdf to perform comprehensive PDF operations including inspection, assembly, page editing, watermarking, rendering, extraction, form filling, encryption, compression, attachments, bookmarks, and metadata management.
      MIT

    TDQS

    A4/5.0

    Scored across 5 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose with no overlap: get_page_image renders visual content, get_page_text extracts textual content, get_pdf_info provides metadata, get_table_of_contents retrieves structural outline, and search_text performs text search. The descriptions reinforce these distinct functions, making tool selection unambiguous.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern with 'get_' or 'search_' prefixes (get_page_image, get_page_text, get_pdf_info, get_table_of_contents, search_text). The naming convention is perfectly uniform across all five tools, using snake_case throughout without any deviations.

    Tool Count5/5

    Five tools is well-scoped for a PDF processing server, covering core operations without bloat. Each tool serves a specific, essential function (rendering, text extraction, metadata, navigation, and search), making the count appropriate and efficient for the domain.

    Completeness4/5

    The toolset covers most fundamental PDF operations well, including reading, extracting, navigating, and searching. A minor gap exists in write/modify operations (e.g., merging, splitting, or annotating PDFs), but the provided tools are sufficient for common agent workflows involving PDF analysis and content retrieval.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues