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glm-vision-mcp

glm-vision-mcp

by SongY1021
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

GLM Vision MCP Server

基于 智谱 GLM-4.6V-Flash 模型的图像识别 MCP 工具。

安装

方式一：PyPI 安装

pip install glm-vision-mcp

方式二：本地安装

git clone <repo-url>
cd glm-vision-mcp
pip install -e .

Related MCP server: Vision MCP

前置条件

  1. 注册 智谱开放平台 账号

  2. 获取 API Key

配置

在 MCP Client 配置文件中添加（如 claude_desktop_config.json 或 .mcp.json）：

{
  "mcpServers": {
    "glm-vision": {
      "command": "uv",
      "args": ["run", "--directory", "<项目路径>", "glm-vision-mcp"],
      "env": {
        "ZHIPU_API_KEY": "your-api-key-here"
      }
    }
  }
}

或 PyPI 安装后：

{
  "mcpServers": {
    "glm-vision": {
      "command": "python",
      "args": ["-m", "glm_vision_mcp.server"],
      "env": {
        "ZHIPU_API_KEY": "your-api-key-here"
      }
    }
  }
}

使用

analyze_image

分析图片内容，支持 URL 和本地文件路径。

参数：

参数

类型

必填

说明

image

string

是

图片 URL（https://...）或本地文件路径

prompt

string

否

自定义分析指令，默认"请详细描述这张图片"

示例：

  • 描述图片：{"image": "https://example.com/photo.jpg"}

  • OCR 提取：{"image": "C:\\screenshots\\receipt.png", "prompt": "提取图中的所有文字"}

  • 图表分析：{"image": "/data/chart.png", "prompt": "分析这个图表的趋势和关键数据"}

Available Tools

1 tool
analyze_imageA

分析图片内容。支持传入图片URL或本地文件路径，可附带自定义分析指令。

NameRequiredDescriptionDefault
imageYes图片URL（以http://或https://开头）或本地文件路径
promptNo对图片的分析指令，默认为'请详细描述这张图片'

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev1.0.0
    • First observedanalyze_image
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of confusion or overlap. The tool's purpose is clearly defined as image analysis, so an agent can unambiguously select it for any image-related task.

Naming Consistency5/5

The single tool 'analyze_image' follows a clean verb_noun pattern, which is consistent with common API naming conventions. While there are no other tools to compare, the name is descriptive and predictable.

Tool Count4/5

The server has only one tool, which is slightly below the typical 3-15 range, but it is tailored specifically for vision-based image analysis. The single tool is reasonably scoped for this narrow purpose, and adding more tools could dilute its focus.

Completeness5/5

The tool covers the core and likely only operation needed for image analysis: accepting an image URL or local path and allowing custom instructions. There are no obvious gaps or dead ends for this domain, as the tool provides a complete workflow for its intended use.

Maintenance

ActivityInactive
ResponsivenessNo recent community issues

Resources

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