# mcp-cogview

> mcp-cogview — superlittlemy-image-mcp. Use this tool when you need to generate images via Zhipu CogView, supporting both synchronous and asynchronous generation with progress updates. It solves problems related to image creation, providing a server-based solution with health check endpoints for reliability. The tool accepts input requests and returns generated images, making it ideal for applications requiring dynamic image generation.

Canonical page: https://skillsregistry.net/skills/superlittlemy-image-mcp  
JSON: https://api.skillsregistry.net/v1/skills/superlittlemy-image-mcp

## Description

MCP server for generating images via Zhipu CogView, supporting synchronous and asynchronous generation with progress notifications, plus health check endpoints.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/o21ffa8yer)
- **Repository:** <https://github.com/Superlittlemy/image_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": "superlittlemy-image-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/superlittlemy-image-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/superlittlemy-image-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