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.
@vlln
Basic information
No overview available yet
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"pdffigures-mcp-server": {
"command": "docker",
"args": [
"build",
"-t",
"pdf-extraction",
"."
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
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.
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>.
It extracts figures, tables, captions, and section titles from PDF documents, particularly from scholarly computer science papers.
Yes, the service can also be run directly using the CLI tool `figure_extractor.py` after setting up the required dependencies.
The default MCP server URL is `http://localhost:5001/mcp`.
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.
Yes, after running the server, navigate to `http://localhost:5001/docs` in a web browser to view the API documentation and test endpoints interactively.

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