# Raster

> Use this tool when you need to manage and organize image libraries efficiently. Raster solves problems related to image storage, retrieval, and sharing by providing a comprehensive interface for browsing, searching, uploading, and transferring images. It accepts image files as input and outputs organized libraries with tagged and searchable images, ideal for use cases where visual content needs to be easily accessible and shared over MCP.

Canonical page: https://skillsregistry.net/skills/app-raster-raster  
JSON: https://api.skillsregistry.net/v1/skills/app-raster-raster

## Description

Browse, search, upload, tag, transfer, and delete images in your Raster libraries over MCP.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** unverified

## Facts

- **Version:** 0.2.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-06-30

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/app.raster%2Fraster)

## Use it

MCP endpoint published by the skill: `https://mcp.raster.app/`

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": "app-raster-raster"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/app-raster-raster` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/app-raster-raster/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