Vision OCR MCP
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Vision OCR MCPOCR my clipboard image"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Vision OCR MCP
本地 RapidOCR(rapidocr + ONNX Runtime,默认免费)+ 通义千问 Qwen-VL(summarize / both)。
能力
mode | 说明 |
| 本地 OCR,中英截图/报错 |
| 通义千问视觉总结(需 API Key) |
| OCR 原文 + 千问总结 |
输入:path 本地路径,或 from_clipboard=true 剪贴板图片。不落盘,结果直接返回给 Agent。
Related MCP server: image-recognition-mcp
安装
cd d:\code\cuosor\skills+mcp\vision-ocr-mcp
python -m pip install -e .
copy .env.example .env
# 编辑 .env,填入 DASHSCOPE_API_KEY(仅 summarize/both 需要)接入 Cursor
编辑用户 MCP 配置(常见路径):%USERPROFILE%\.cursor\mcp.json
{
"mcpServers": {
"vision-ocr": {
"command": "D:\\Anaconda3-new\\python.exe",
"args": ["-m", "vision_ocr_mcp"],
"cwd": "d:\\code\\cuosor\\skills+mcp\\vision-ocr-mcp",
"env": {
"DASHSCOPE_API_KEY": "sk-你的密钥",
"QWEN_VL_MODEL": "qwen-vl-plus",
"PYTHONPATH": "d:\\code\\cuosor\\skills+mcp\\vision-ocr-mcp\\src"
}
}
}
}若已 pip install -e .,可去掉 PYTHONPATH,command 用安装了该包的同一个 Python。
改完后重启 Cursor / 重载 MCP。对话里可说:
「用 vision-ocr 读这张图
D:\xxx.png」「从剪贴板 OCR」
「用 summarize 总结这张架构图」
费用
OCR:本地,免费
千问:按 Token;新用户常有免费额度,见阿里云百炼控制台
云端高精度 OCR 未接入,可后续再加。
This server cannot be deployed
Maintenance
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