# Optical Context MCP

> Use this tool when you need to efficiently process long visual documents, such as OCR-heavy PDFs, by compressing them into dense packed images. This solves problems of slow agent processing times and large file sizes, enabling faster and more reliable document analysis. It takes PDF inputs and outputs compressed images, ideal for use cases involving large-scale document processing and analysis.

Canonical page: https://skillsregistry.net/skills/io-github-chrboebel-optical-context-mcp  
JSON: https://api.skillsregistry.net/v1/skills/io-github-chrboebel-optical-context-mcp

## Description

Compress OCR-heavy PDFs into dense packed images so agents can work with long visual documents.

## Trust

- **Trust score (0–1):** 0.83
- **Verification tier:** verified
- **Last scanned:** 2026-08-28

## Facts

- **Version:** 0.1.2
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-08-28

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/io.github.ChrBoebel%2Foptical-context-mcp)
- **Repository:** <https://github.com/ChrBoebel/optical-context-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": "io-github-chrboebel-optical-context-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/io-github-chrboebel-optical-context-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/io-github-chrboebel-optical-context-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