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
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使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"pdffigures-mcp-server": {
"command": "docker",
"args": [
"build",
"-t",
"pdf-extraction",
"."
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
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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