glm-vision-mcp-server
The glm-vision-mcp-server provides AI-powered visual understanding using ZhipuAI's GLM vision models. It can:
Analyze a single local or remote image (up to 10MB) and generate a detailed Chinese description.
Compare multiple images, describing each individually and highlighting similarities and differences.
Answer specific questions about one or more images when given an optional question parameter, with responses in Chinese.
Switch between the free
glm-4.6v-flashmodel and the paidglm-4.6vmodel via an environment variable.Integrate as an MCP server for Claude Code, enabling seamless tool calling and automatic triggering (e.g., when pasting images).
Note: Image content is sent to ZhipuAI's API; avoid sensitive information.
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-server描述这张图片的内容"
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-server
基于智谱免费视觉模型 glm-4.6v-flash 的 MCP 服务器:理解本地图片或网络图片,返回中文描述或回答问题。
配套 Skill:~/.claude/skills/glm-vision/SKILL.md(贴图自动触发)。
效果展示
测试 1:GitHub 项目页面识别(左:输入图 → 右:GLM 识别结果)
输入 | 识别结果 |
测试 2:音乐播放器界面识别(左:输入图 → 右:GLM 识别结果)
输入 | 识别结果 |
Related MCP server: MCP Image Recognition Server
快速开始
仓库内已含 Skill 副本(
.claude/skills/glm-vision/SKILL.md),修改后需同步复制到用户目录才生效。
# 1. 安装依赖(将下方路径替换为你实际的安装目录)
cd C:/Users/ASUS/.claude/mcp-servers/glm-vision-mcp-server
uv sync
# 2. 全局注册 MCP(stdio,--scope user 使其在任何项目可用)
claude mcp add vision --scope user --env ZHIPUAI_API_KEY=<你的key> -- uv run --directory C:/Users/ASUS/.claude/mcp-servers/glm-vision-mcp-server glm-vision-mcp
# 3. 安装 Skill(贴图自动触发,任何项目可用;已装过可跳过)
mkdir -p ~/.claude/skills/glm-vision
cp .claude/skills/glm-vision/SKILL.md ~/.claude/skills/glm-vision/SKILL.md
# 4. 重启 Claude Code 会话使 MCP 与 Skill 生效API key 获取:https://open.bigmodel.cn/ (注册后「API Keys」页面创建,模型 glm-4.6v-flash 免费)。
工具
工具 | 参数 | 说明 |
|
| 理解图片;单图自动描述、多图对比分析;传入问题则回答 |
隐私声明
⚠️ 调用本工具时,图片内容(本地图片 base64 编码或 URL)会发送至智谱 AI 的 API(open.bigmodel.cn,国内服务器)用于视觉理解。请勿向本工具传入包含敏感信息的截图(账号密码、身份证、聊天记录等)。如需自托管,请自行更换模型服务商(见「更换底层视觉模型」)。
开发
uv run pytest -v # 单元测试(mock 网络)配置
ZHIPUAI_API_KEY:智谱 API key(环境变量,勿硬编码)GLM_VISION_MODEL:底层视觉模型 ID(可选,默认glm-4.6v-flash)图片限制:本地文件最大 10MB
更换底层视觉模型
原因:本服务器通过智谱的 OpenAI 兼容接口调用模型——鉴权方式、请求格式(content 数组、image_url/base64 传输)、响应结构对所有 glm 系列模型完全一致,底层模型只由请求中的 model 字段决定。因此更换模型 ID 即可无痛切换视觉模型,代码、Skill、MCP 注册均无需改动。
用法(设置环境变量 GLM_VISION_MODEL 即可):
# 免费版(默认值,不设置时生效)
export GLM_VISION_MODEL=glm-4.6v-flash
# 付费版 glm-4.6v(访问更稳定、限流更少,适合生产使用)
export GLM_VISION_MODEL=glm-4.6v已在 claude mcp add 注册过的场景,重新注册并把模型带入 MCP 环境变量:
claude mcp add vision --scope user \
--env ZHIPUAI_API_KEY=<你的key> \
--env GLM_VISION_MODEL=glm-4.6v \
-- uv run --directory C:/Users/ASUS/.claude/mcp-servers/glm-vision-mcp-server glm-vision-mcp或直接改代码中 glm_client.py 的 DEFAULT_MODEL 常量(改后需重装/重启生效)。
常见问题
免费模型会间歇性限流(HTTP 429):提示"该模型当前访问量过大,请您稍后再试"是智谱免费模型(glm-4.6v-flash)的时段性共享配额限制,不是代码或配置问题。处理方式:
稍后重试:等待 15 秒以上再次调用(限流是时段性的,低谷时段即恢复,通常重试 1-2 次即可)
切换付费模型:设置
GLM_VISION_MODEL=glm-4.6v绕过免费配额,访问更稳定(见「更换底层视觉模型」)
修改工具代码后需退出并重新启动 Claude Code 才会生效:MCP 服务器进程在会话启动时加载,会话期间运行的始终是启动时的代码版本。改动 glm_client.py / server.py / Skill 后,需退出当前 Claude Code 会话并重新启动,工具才会运行新代码;claude mcp list 可查看服务器连接状态。
Maintenance
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Tools
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