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Let an LLM read local PDF text and positional structure over stdio.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "PDF MCP Server" yet — see the docs or source repo.
Please read the local file ./reports/annual-report.pdf, extract the full text, and output it page by page.
Returns the PDF text content organized by page.
Please read ./docs/spec.pdf and return the text plus positional structure for later layout analysis.
Returns the text content together with its positional structure.
Read the local PDF ./papers/method.pdf and extract text and page structure for downstream Q&A.
Outputs PDF text and structured positional information that an LLM can use.
Developers building an MCP integration can use it to pass PDF content from local disk to an LLM host. It provides both text and positional structure, not just plain text.
In research or document-processing workflows, this tool can return where text appears within the PDF. That is useful for later citation, locating content, or layout analysis.
It reads PDF files from local disk and returns their text and positional structure to an LLM host over stdio. Its core purpose is to give an LLM access to PDF content plus layout-related position data.
The provided information only says it reads PDF files from local disk. For support of online URLs, see the source repository.
The available material only states that it communicates with the LLM host over stdio and does not include installation steps. For exact setup and runtime details, see the source repository.
Enable AI to read PDFs, extract content, and search specific information.
Expose PDF files page by page over HTTP for AI and programmatic access.
Lets AI inspect PDF text layers, outlines, and page content locally.
Help AI parse PDFs, search semantically, and navigate documents intelligently.
Convert PDFs into citeable structured content for parsing, extraction, Q&A, and rendering.
A fast MCP tool for reading, parsing, and processing PDF documents.