images-handler
Click on "Install 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., "@images-handlerDescribe the image I sent"
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.
images-handler
给只支持文本的模型(如 DeepSeek)补上"看图"能力的标准 MCP 服务。
DeepSeek 不能直接识别图片,但本服务通过 Cursor TypeScript SDK 在本机跑一个 Cursor agent(默认 composer-2,可换 Claude/GPT 视觉模型),把图片理解成文本描述返回。DeepSeek 调用工具拿到文字结果,就等于"能看图"了。
本服务只做图片识别:agent 始终以纯文本模式运行,不执行任何 shell/文件工具。
前置条件
Node.js ≥ 22.13
Cursor 凭据(二选一):
设置环境变量
CURSOR_API_KEY,或已用
Cursor.auth.login()登录过 Cursor 账号(SDK 自动读取存储的凭据)
Related MCP server: DeepSeek Eyes
安装与运行
npm install
npm start # 开发运行(stdio),等价 npx tsx src/index.ts
# 或构建后运行
npm run build && node dist/index.js环境变量
变量 | 默认 | 说明 |
| — | Cursor API key,缺省时回退登录态 |
|
| 视觉模型 id |
|
| 单次识别调用超时(毫秒) |
接入客户端
Claude Code
claude mcp add image-recognition -e CURSOR_API_KEY="${CURSOR_API_KEY}" -- npx tsx D:/path/to/images-handler/src/index.tsCursor
.cursor/mcp.json:
{
"mcpServers": {
"image-recognition": {
"command": "npx",
"args": ["tsx", "D:/path/to/images-handler/src/index.ts"],
"env": {
"CURSOR_API_KEY": "${CURSOR_API_KEY}"
}
}
}
}其他标准 MCP 客户端
stdio 传输,按标准协议配置启动命令即可(记得通过 env 传入 CURSOR_API_KEY)。
工具:recognize_image
参数 | 类型 | 必填 | 说明 |
| string 或 string[] | 是 | 图片 data URI( |
| string | 否 | 想针对图片问什么,缺省为"请详细描述这张图片的内容、画面元素和任何可见文字。" |
| string | 否 | 覆盖视觉模型(默认 |
示例
{
"images": ["data:image/png;base64,iVBORw0KGgo..."]
}带自定义指令:
{
"images": ["data:image/png;base64,iVBORw0KGgo..."],
"instruction": "识别图中的文字并翻译成中文"
}传本地文件路径(在服务所在机器上读取):
{
"images": ["D:/photos/screenshot.png"]
}说明与限制
每次工具调用都会新建一个独立 Cursor agent(调用间不共享会话历史),用完即关闭。
服务只做图片识别:agent 恒为纯文本模式(
tools: []),不执行 shell/文件工具,除传入的图片外不会读取或访问任何本地内容。传本地路径时,文件在服务所在机器上读取,并按扩展名识别为图片;非图片扩展名会被拒绝。请仅传入你自己信任的图片路径。
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