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Pdf(paper) Figures Extraction Mcp Serever

@vlln

Repository

About Pdf(paper) Figures Extraction Mcp Serever

No overview available yet

#pdf#figure-extraction#mcp-server

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "pdffigures-mcp-server": {
      "command": "docker",
      "args": [
        "build",
        "-t",
        "pdf-extraction",
        "."
      ]
    }
  }
}

Tools

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We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Pdf(paper) Figures Extraction Mcp Serever?

Pdf(paper) Figures Extraction Mcp Serever is a FastAPI-based service that extracts figures, tables, captions, and section titles from PDF documents. It wraps PDFFigures 2.0, a figure extraction system by the Allen Institute for AI designed for scholarly computer science papers, and exposes the functionality as both an HTTP API and an MCP tool for integration with AI agents and workflows.

How to use Pdf(paper) Figures Extraction Mcp Serever?

Deploy using Docker: clone the repository, build the image, and run the container. After deployment, send a POST request to /api/extract with a PDF file or a PDF URL. The MCP tool (extract_figures_from_pdf) can be invoked via an HTTP request to the /mcp endpoint. The CLI can also be used directly via python figure_extractor.py <path_to_pdf>.

Key features of Pdf(paper) Figures Extraction Mcp Serever

  • Extracts figures, tables, captions, and section titles from PDFs
  • Supports both local and remote PDF files
  • Provides statistics of extracted tables and figures
  • Docker support for easy deployment and scalability
  • Offers visualization options for PDF parsing
  • MCP server exposes extraction as a tool for AI agents

Use cases of Pdf(paper) Figures Extraction Mcp Serever

  • Machine learning dataset creation from clinical trial reports and research papers
  • Clinical research data mining for automated figure and table cataloging
  • Academic literature review and education for compiling visual libraries

FAQ from Pdf(paper) Figures Extraction Mcp Serever

What types of content does Pdf(paper) Figures Extraction Mcp Serever extract?

It extracts figures, tables, captions, and section titles from PDF documents, particularly from scholarly computer science papers.

Can I use Pdf(paper) Figures Extraction Mcp Serever without Docker?

Yes, the service can also be run directly using the CLI tool figure_extractor.py after setting up the required dependencies.

What is the default MCP server URL?

The default MCP server URL is http://localhost:5001/mcp.

What is PDFFigures 2.0 and how does this server relate?

PDFFigures 2.0 is a Scala-based project by the Allen Institute for AI that extracts figures from scholarly documents. This server serves as a Python-FastAPI wrapper around that system, providing an HTTP interface and an MCP tool.

Is there a way to test the API after deployment?

Yes, after running the server, navigate to http://localhost:5001/docs in a web browser to view the API documentation and test endpoints interactively.

Frequently asked questions

What types of content does Pdf(paper) Figures Extraction Mcp Serever extract?

It extracts figures, tables, captions, and section titles from PDF documents, particularly from scholarly computer science papers.

Can I use Pdf(paper) Figures Extraction Mcp Serever without Docker?

Yes, the service can also be run directly using the CLI tool `figure_extractor.py` after setting up the required dependencies.

What is the default MCP server URL?

The default MCP server URL is `http://localhost:5001/mcp`.

What is PDFFigures 2.0 and how does this server relate?

PDFFigures 2.0 is a Scala-based project by the Allen Institute for AI that extracts figures from scholarly documents. This server serves as a Python-FastAPI wrapper around that system, providing an HTTP interface and an MCP tool.

Is there a way to test the API after deployment?

Yes, after running the server, navigate to `http://localhost:5001/docs` in a web browser to view the API documentation and test endpoints interactively.

Comments

Basic information

Category

Data & Analytics

Transports

stdio

Author

vlln

Submitted by

赵刚

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