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MCP Servers/sylphlab pdf reader mcp

Data · MODEL CONTEXT PROTOCOL

sylphlab pdf reader mcp

An MCP server built with Node.js/TypeScript that allows AI agents to securely read PDF files (local or URL) and extract text, metadata, or page counts. Uses pdf-parse.

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WHAT IT CONNECTS

What sylphlab pdf reader mcp gives an AI Agent

  • Read full text content from PDF files.
  • Read text content from specific pages or page ranges.
  • Read PDF metadata (author, title, creation date, etc.).
  • Get the total page count of a PDF.
  • Process multiple PDF sources (local paths or URLs) in a single request.
  • Securely operates within the defined project root.
  • Provides structured JSON output via MCP.
  • Available via npm and Docker Hub.
  • **Documentation:**
  • Finalize all documentation sections (Guide, API, Design, Comparison).
  • Resolve TypeDoc issue and generate API documentation.
  • Add more examples and advanced usage patterns.
  • Implement PWA support and mobile optimization for the docs site.
  • Add share buttons and growth metrics to the docs site.
  • **Benchmarking:**
  • Conduct comprehensive benchmarks with diverse PDF files (size, complexity).
  • Measure memory usage.
  • Compare URL vs. local file performance.
  • **Core Functionality:**
  • Explore potential optimizations for very large PDF files.
  • Investigate options for extracting images or annotations (longer term).
  • **Testing:**
  • Increase test coverage towards 100% where practical.
  • Add runtime tests once feasible.
  • **Found a bug or have a feature request?** Please open an issue on [GitHub Issues](https://github.com/sylphlab/pdf-reader-mcp/issues).
  • **Want to contribute?** We welcome contributions! Please see [CONTRIBUTING.md](./CONTRIBUTING.md).
  • **Star & Watch:** If you find this project useful, please consider starring ⭐ and watching 👀 the repository on [GitHub](https://github.com/sylphlab/pdf-reader-mcp) to show your support and stay updated!

SECURITY

An MCP listing is not a security review

An MCP server may receive model context, credentials, local files, or permission to call external systems. Review its code, requested environment variables, network behavior, package provenance, and maintenance status before connecting it to an agent.