by jztan · MCP Server · ★ 116
pdf-mcp Surgical PDF access for AI agents — search, read, and extract without flooding context. A Model Context Protocol (MCP) server that enables AI agents to read, search, and extract content from PDF files. Built with Python and PyMuPDF, with SQLite-based caching for persistence across server restarts. mcp-name: io.github.jztan/pdf-mcp Try it in your browser See what your AI agent sees → Drop in any PDF and watch an agent skim it, search it, and read only the pages that matter — using a fraction of the tokens. 100% client-side, no install required.
| Stars | 116 |
| Forks | 8 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 81.3392335563874/100 |
| Open Issues | 1 |
| Last Updated | 2026-08-23 |
| Created | 2026-01-28 |
| Platforms | claude-code, cli, codex, mcp, python |
| Est. Tokens | ~17k |
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pdf-mcp is MCP server that lets Claude Code and other AI agents work through large PDFs, and whole folders of them, without overflowing context: hybrid semantic + keyword search, selective page reading, tables, . It is categorized as a MCP Server with 116 GitHub stars.
pdf-mcp is primarily written in Python. It covers topics such as agentic-rag, ai, cjk.
You can find installation instructions and usage details in the pdf-mcp GitHub repository at github.com/jztan/pdf-mcp. The project has 116 stars and 8 forks, indicating an active community.
pdf-mcp is released under the MIT license, making it free to use and modify according to the license terms.