Nano PDF MCP

A memory-efficient Model Context Protocol (MCP) server for reading and splitting large PDF files.
Built with fastmcp and pymupdf (PyMuPDF).

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Tools

Tool	Description
`get_pdf_info`	Retrieves file metadata and total page count — Use this before calling read_pdf
`read_pdf`	Extracts text by streaming the specified page range
`split_pdf`	Creates a new PDF with only the specified pages
`save_markdown_summary`	Saves AI-summarized content to a `.md` file

Recommended Workflow

1. get_pdf_info(filepath) → Check total page count
2. read_pdf(filepath, start_page, end_page) → Read text
3. save_markdown_summary(output_filepath, markdown_content) → Save summary

Installation

No need to clone or install locally!
If uv is installed, it runs instantly with a single command below.

Installing `uv` (If not installed)

macOS / Linux:

curl -LsSf https://astral.sh/uv/install.sh | sh

Windows:

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Claude Desktop

Add the following to your claude_desktop_config.json:

{
  "mcpServers": {
    "nano-pdf-mcp": {
      "command": "uvx",
      "args": ["nano-pdf-mcp"]
    }
  }
}

Antigravity

Add the following to your .gemini/settings.json:

{
  "mcpServers": {
    "nano-pdf-mcp": {
      "command": "uvx",
      "args": ["nano-pdf-mcp"]
    }
  }
}

Architecture

Memory Efficiency: Streams and processes large PDFs page by page (no full loading into memory)
Fast Splitting: Copies only C-level pointers via insert_pdf — no re-encoding
Safe Logging: All logs are output to stderr (prevents stdio communication pollution)
Clear Errors: Instantly returns error messages for invalid ranges/paths