by jztan · MCP Server · ★ 74
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 | 74 |
| Forks | 8 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 80.3187320185016/100 |
| Last Updated | 2026-07-07 |
| Created | 2026-01-28 |
| Platforms | claude-code, cli, codex, mcp, python |
| Est. Tokens | ~17k |
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pdf-mcp is An MCP server that lets Claude Code and other AI agents work through large PDFs without overflowing their context — search by meaning or keyword, read only the pages that matter, and cleanly pull out . It is categorized as a MCP Server with 74 GitHub stars.
pdf-mcp is primarily written in Python. It covers topics such as agentic-ai, 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 74 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.