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thincher avatar

Minimax Understand Image

thincher/awsome_skills
371 installs1 stars
Summary

This connects Claude to MiniMax's image understanding API through their MCP server. You can analyze images from local paths or URLs by asking questions about them in natural language, like "describe what's in this image" or "what objects do you see here." The skill handles the full setup workflow including uvx installation, API key configuration through environment variables or a config file, and provides a Python script that communicates with the MCP server over stdio. It's aimed at Chinese developers based on the bilingual documentation and includes mirror options for PyPI package installation. Worth noting that you need a MiniMax subscription to use it, and the setup is a bit involved for first-time use though subsequent calls are straightforward.

Install to Claude Code

npx -y skills add thincher/awsome_skills --skill minimax-understand-image --agent claude-code

Installs into .claude/skills of the current project.

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Files
SKILL.mdView on GitHub

minimax-understand-image

使用 MiniMax MCP 服务器进行图像理解和分析。

执行流程(首次需要安装,后续直接步骤4调用)

步骤 1: 检查并安装依赖

1.1 检查 uvx 是否可用
which uvx

如果不存在,安装 uv:

方法 1: 使用官方安装脚本(推荐)

curl -LsSf https://astral.sh/uv/install.sh | sh

方法 2: 使用国内镜像加速(如果官方脚本下载失败)

临时使用清华镜像源安装:

export UV_INDEX_URL="https://pypi.tuna.tsinghua.edu.cn/simple"
curl -LsSf https://astral.sh/uv/install.sh | sh

或者临时使用阿里云镜像源:

export UV_INDEX_URL="https://mirrors.aliyun.com/pypi/simple/"
curl -LsSf https://astral.sh/uv/install.sh | sh
1.2 检查 MCP 服务器是否已安装
uvx minimax-coding-plan-mcp --help

执行命令判断是否MCP服务器已安装, 如果安装了跳到步骤 2。

1.3 安装 MCP 服务器(如果未安装)

方法 1: 使用默认源安装

uvx install minimax-coding-plan-mcp

方法 2: 使用国内镜像加速(如果默认源下载失败)

临时使用清华镜像源:

export UV_INDEX_URL="https://pypi.tuna.tsinghua.edu.cn/simple"
uvx install minimax-coding-plan-mcp

或者临时使用阿里云镜像源:

export UV_INDEX_URL="https://mirrors.aliyun.com/pypi/simple/"
uvx install minimax-coding-plan-mcp

步骤 2: 检查 API Key 配置

cat ~/.openclaw/config/minimax.json 2>/dev/null | python3 -c "import json,sys; d=json.load(sys.stdin); print(d.get('api_key', ''))"

如果返回非空的 API Key,跳到步骤 4。

步骤 3: 配置 API Key(如果未配置)

3.1 从环境变量获取 API Key
echo $MINIMAX_API_KEY

如果返回非空的 API Key,跳到步骤 3.3

3.2 如果没有找到 Key,向用户索要

直接询问用户提供 MiniMax API Key。 如果未购买MiniMax,购买地址为: https://platform.minimaxi.com/subscribe/coding-plan?code=GjuAjhGKqQ&source=link

3.3 保存 API Key
mkdir -p ~/.openclaw/config
cat > ~/.openclaw/config/minimax.json << EOF
{
  "api_key": "API密钥",
  "output_path": "~/.openclaw/workspace/minimax-output"
}
EOF

步骤 4: 使用 MCP 处理图像

4.1 准备图片

将图片放到可访问路径,例如:

  • ~/.openclaw/workspace/images/图片名.jpg
  • 或者使用 URL
4.2 调用 understand_image

使用脚本调用 MCP 服务:

python3 {curDir}/scripts/understand_image.py <图片路径或URL> "<对图片的提问>"

示例:

# 描述图片内容
python3 {curDir}/scripts/understand_image.py ~/image.jpg "详细描述这张图片的内容"

# 使用 URL
python3 {curDir}/scripts/understand_image.py "https://example.com/image.jpg "这张图片展示了什么?"
4.3 API 参数说明
参数说明类型
image图片路径或 URLstring (必填)
prompt对图片的提问string (必填)

脚本说明

脚本位置:{curDir}/scripts/understand_image.py

功能:

  • 优先从环境变量 MINIMAX_API_KEY 读取 API Key,如果没有则从 ~/.openclaw/config/minimax.json 读取
  • 通过 stdio 模式启动 MCP 服务器
  • 发送 JSON-RPC 请求调用 understand_image 工具
  • 返回格式化的 JSON 结果

错误处理:

  • API Key 未配置时提示错误
  • uvx 未安装时提示安装命令
  • MCP 服务器错误时显示 stderr 输出
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Categories
AI & Agent Building
First SeenJun 3, 2026
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