# DeepSeek Vision MCP

> DeepSeek Vision MCP — zunyiqingfeng-code-deepseek-vision-mcp. Use this tool when you need to analyze images using a text-only Large Language Model (LLM), enabling capabilities such as single or multiple image analysis, batch processing, and screen capture. It solves problems of image understanding and processing for LLMs, providing outputs such as text-based descriptions and insights. Ideal for use cases where visual data needs to be integrated with text-based AI models, with inputs including images and screen captures, and outputs in text format.

Canonical page: https://skillsregistry.net/skills/zunyiqingfeng-code-deepseek-vision-mcp  
JSON: https://api.skillsregistry.net/v1/skills/zunyiqingfeng-code-deepseek-vision-mcp

## Description

Enables text-only LLMs to analyze images by bridging DeepSeek's web vision chat via MCP, supporting single/multiple image analysis, batch glob processing, and Windows screen capture for any MCP client.

## Trust

- **Trust score (0–1):** 0.66
- **Verification tier:** scanned
- **Last scanned:** 2026-08-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-08-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/uctd8k1fqx)
- **Repository:** <https://github.com/zunyiqingfeng-code/deepseek-vision-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": "zunyiqingfeng-code-deepseek-vision-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/zunyiqingfeng-code-deepseek-vision-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/zunyiqingfeng-code-deepseek-vision-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