vision-mcp-ms

vision-mcp-ms

A cloud vision MCP server that enables text-only LLMs like DeepSeek to analyze images via OpenAI-compatible APIs (e.g., SiliconFlow), offering a single analyze_image tool with support for URL/data URLs and automatic model fallback.

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README

vision-mcp-ms

云端视觉 MCP 服务：通过 OpenAI 兼容接口（默认硅基流动 SiliconFlow）分析图片， 为 DeepSeek 这类纯文本大模型提供「看图」能力。

  • 单一工具 analyze_image(image, prompt)
  • 支持 HTTP(S) 图片 URL 和 base64 data URL
  • 多模型按顺序自动 fallback（限流 / 超时 / 5xx 时切下一个）
  • 纯 API 调用、不依赖本地环境，可部署到魔搭 MCP 广场云端托管

环境变量

变量 必填 默认值 说明
OPENAI_API_KEY 是* - API Key（也兼容 SILICONFLOW_API_KEY / API_KEY）
OPENAI_BASE_URL 否 https://api.siliconflow.cn/v1 OpenAI 兼容接口地址
VISION_MODELS 否 Qwen/Qwen2.5-VL-7B-Instruct 逗号分隔的有序模型列表，靠前的优先
VISION_REQUEST_TIMEOUT_MS 否 60000 单次模型请求超时（毫秒）

* 部署时在魔搭 / MCP 客户端的 env 里配置。

本地使用（stdio）

在 MCP 客户端（Cherry Studio 桌面版等）里添加：

{
  "mcpServers": {
    "vision-mcp-ms": {
      "command": "uvx",
      "args": ["vision-mcp-ms"],
      "env": {
        "OPENAI_API_KEY": "sk-你的硅基流动Key",
        "OPENAI_BASE_URL": "https://api.siliconflow.cn/v1",
        "VISION_MODELS": "Qwen/Qwen2.5-VL-7B-Instruct,Qwen/Qwen2.5-VL-72B-Instruct"
      }
    }
  }
}

本地 stdio 模式下，image 参数也支持本地文件绝对路径（如 D:\Pictures\a.png）。 云端托管模式下仅支持 URL / data URL（服务端读不到你的本地文件）。

开发 / 测试

uv sync                     # 建环境
uv run python -m vision_mcp # 以 stdio 模式启动
uv run python -c "from vision_mcp.server import _to_data_url; print(_to_data_url('https://httpbin.org/image/jpeg')[:40])"

发布到 PyPI

cd vision-mcp-ms
uv run python -m build
uv run twine upload dist/*.whl

部署到魔搭 MCP 广场（云端托管）

  1. 把代码推到 GitHub 仓库（或发布到 PyPI 后）。
  2. 打开 https://www.modelscope.cn/mcp/servers/create?template=customize
  3. 托管类型选「可托管部署」，来源选你的 GitHub 仓库 / PyPI 包。
  4. 配置 command / args（如 uvx / vision-mcp-ms），在 env 里填 OPENAI_API_KEY、OPENAI_BASE_URL、VISION_MODELS。
  5. 创建后魔搭会自动部署，得到一个 HTTP 地址，填入手机 MCP 客户端即可。

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