glm-vision-mcp
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., "@glm-vision-mcp把这张截图里的文字提取出来"
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.
glm-vision-mcp
基于智谱 AI 开放平台免费视觉模型 GLM-4.6V-Flash 的 MCP server,为 AI 助手提供图像识别与 OCR 能力。
图像理解(看图问答、描述、识别物体/场景)
OCR 文字提取(截图、票据、文档、界面文案)
图片输入支持 URL、base64 data URI、本地文件路径 三种方式
支持思考模式开关(
thinking参数),复杂分析可开启
工具
工具 | 说明 | 参数 |
| 通用图像识别/理解 |
|
| OCR 文字提取,按原始版式输出 |
|
image 支持三种格式:
https://example.com/photo.jpg # 公开图片 URL
data:image/png;base64,iVBORw0... # base64 data URI
C:\Users\me\Desktop\截图.png # 本地文件路径(≤10MB)Related MCP server: Image Description MCP Server
一、获取免费 API Key(一次性)
打开 智谱 AI 开放平台 注册账号并完成实名认证
进入 API Keys 页面 → 点击「创建 API Key」→ 复制生成的 key(形如
xxxxx.xxxxx)GLM-4.6V-Flash 本身免费调用,新用户注册还赠送体验额度,无需充值
二、配置 API Key(Windows)
方式 A(推荐):系统环境变量
# 在 PowerShell / CMD 执行(之后需新开终端或重启 Reasonix 才生效)
setx ZHIPU_API_KEY "你的key"方式 B:仅当前会话
$env:ZHIPU_API_KEY = "你的key" # PowerShell 临时设置⚠️ 不要把 key 直接写进
.mcp.json或config.toml——项目已用${ZHIPU_API_KEY}占位符,从环境变量读取,避免 key 落盘泄露。
三、安装与注册
npm install # 安装依赖(仅需一次)
node src/index.js # 手动启动(MCP 客户端会自动拉起,一般无需手动运行)本项目已注册为 Reasonix 全局 MCP(配置在 %APPDATA%\reasonix\config.toml),
本机所有项目都可直接使用。如需重新注册或卸载:
# 重新注册(读取 .mcp.json)
# 在 Reasonix 对话中使用 install_source 工具,source 指向本目录的 .mcp.json,scope=global
# 卸载
# install_source op=uninstall,name=glm-vision-mcp四、使用示例
注册完成后,直接在对话里告诉 AI「看」图即可,例如:
帮我识别这张图片:C:\Users\me\Desktop\票据.png
把这张截图里的文字提取出来:https://example.com/receipt.png
这张图里有什么异常?data:image/png;base64,……AI 会自动调用 analyze_image / extract_text 工具完成识别。
五、注意事项(免费模型限流)
GLM-4.6V-Flash 免费版在高峰期可能遇到平台过载,API 返回
HTTP 429 / 错误码 1305(该模型当前访问量过大)。处理建议:
稍等 30–90 秒再重试,避免连续高频请求(平台文档明确建议)
识别任务间留出间隔;并发任务可考虑排队
这不是 key 或代码问题,是平台侧的临时保护
六、开发与测试
npm test # 单元测试(图像输入处理)+ MCP 冒烟测试(不需要 key)
ZHIPU_API_KEY=xxx node test/e2e.mjs # 端到端真实识别测试(需要 key)
ZHIPU_API_KEY=xxx node test/e2e.mjs --which=url # 只测 extract_text(URL)
ZHIPU_API_KEY=xxx node test/e2e.mjs --which=local # 只测 extract_text(本地路径)项目结构
src/index.js # MCP server 入口:注册 analyze_image / extract_text
src/zhipu.js # 智谱 chat/completions 封装(内置 fetch、超时、中文错误)
src/image-input.js # 图像输入统一处理(URL / data URI / 本地路径,≤10MB)
test/ # 单元测试、冒烟测试、端到端测试
.mcp.json # MCP 注册描述This server cannot be installed
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