glm-vision-mcp
封装智谱 GLM-4.6V-Flash(免费视觉模型)的 MCP 服务器,向任意 MCP 客户端暴露一个 analyze_image 工具,支持单图/多图分析、OCR、多图对比。
特性
| 能力 | 说明 |
|---|---|
| 图片分析 | 本地路径 / http(s) URL / base64 data URI 均可,自动转 data URI |
| 多图对比 | 多张图片一次传入,按 prompt 对比分析 |
| 限流韧性 | 429 / 1302 / 1305 指数退避重试 → 多 Key 轮询 → 降级备用模型 glm-4.1v-thinking-flash |
| 配置自查 | check_config 工具检查 Key/模型/端点,不泄露 Key |
环境要求
- Python >= 3.10
- 智谱开放平台 API Key(https://open.bigmodel.cn/usercenter/apikeys),
glm-4.6v-flash免费 - 想进一步降低限流概率,可注册多个账号各取一个 Key,配置时用英文逗号分隔
安装
cd glm-vision-mcp
python -m venv .venv
.venv\Scripts\pip install -r requirements.txt
启动
# stdio 模式(MCP 客户端默认方式)
$env:ZHIPU_API_KEY = "你的Key"
.venv\Scripts\python server.py
# SSE 调试模式(无鉴权,仅限本机)
.venv\Scripts\python server.py --sse 8090
客户端配置
Codex(~/.codex/config.toml)
[mcp_servers.glm-vision]
command = "C:\\绝对路径\\glm-vision-mcp\\.venv\\Scripts\\python.exe"
args = ["C:\\绝对路径\\glm-vision-mcp\\server.py"]
[mcp_servers.glm-vision.env]
ZHIPU_API_KEY = "你的Key"
# GLM_VISION_MODELS = "glm-4.6v-flash"
# GLM_API_BASE = "https://open.bigmodel.cn/api/paas/v4/chat/completions"
Claude Desktop(claude_desktop_config.json)
{
"mcpServers": {
"glm-vision": {
"command": "C:\\绝对路径\\glm-vision-mcp\\.venv\\Scripts\\python.exe",
"args": ["C:\\绝对路径\\glm-vision-mcp\\server.py"],
"env": { "ZHIPU_API_KEY": "你的Key" }
}
}
}
工具接口
analyze_image(images, prompt, temperature, max_tokens, thinking)
| 参数 | 类型 | 必填 | 说明 |
|---|---|---|---|
images |
string[] | 是 | 本地路径 / http(s) URL / data URI |
prompt |
string | 否 | 分析要求,默认“请详细描述这张图片的内容” |
temperature |
number | 否 | 0.0~1.0,默认 0.7 |
max_tokens |
integer | 否 | 最大输出 token,默认 2048 |
thinking |
boolean | 否 | 深度思考模式,默认 false |
环境变量
| 变量 | 必填 | 说明 |
|---|---|---|
ZHIPU_API_KEY |
是 | 智谱 API Key,逗号分隔支持多 Key 轮询 |
GLM_VISION_MODELS |
否 | 模型优先级,逗号分隔,默认 glm-4.6v-flash,glm-4.1v-thinking-flash |
GLM_API_BASE |
否 | 覆盖 API 端点 |
注意事项
- 本地图片单张 ≤ 10MB,支持 jpg/jpeg/png/webp/gif/bmp
- 免费模型高峰期可能限流,全部 Key + 全部模型都限流时才报错,稍等 15~30 秒错峰重试
- 401/400 等非限流错误不降级不重试,直接返回,便于定位配置问题
验证
# 离线检查(不联网)
.venv\Scripts\python test_smoke.py
# 联网冒烟:MCP 握手 + analyze_image 真实调用
$env:ZHIPU_API_KEY = "你的Key"
.venv\Scripts\python test_smoke.py --live
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