# nano-pdf-mcp

> Use this tool when you need to efficiently process large PDF files by splitting them into individual pages. The nano-pdf-mcp server solves the problem of memory-intensive PDF processing, allowing for memory-efficient reading and splitting of files page by page. It takes large PDF files as input and outputs individual pages, ideal for use cases where processing massive documents is required.

Canonical page: https://skillsregistry.net/skills/eren0315-nano-pdf-mcp  
JSON: https://api.skillsregistry.net/v1/skills/eren0315-nano-pdf-mcp

## Description

Memory-efficient MCP server for reading and splitting large PDF files page by page using PyMuPDF.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** file-system
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/hjmr5rxgtt)
- **Repository:** <https://github.com/eren0315/nano-pdf-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "eren0315-nano-pdf-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/eren0315-nano-pdf-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/eren0315-nano-pdf-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt