MCP Server GLM Vision

A Model Context Protocol (MCP) server that integrates GLM-4.5V from Z.AI with Claude Code.

Features

Image Analysis: Analyze images using GLM-4.5V's vision capabilities
Local File Support: Analyze local image files or URLs
Configurable: Easy setup with environment variables

Installation

Prerequisites

Python 3.10 or higher
GLM API key from Z.AI
Claude Code installed

Setup

Clone or create the project directory:
cd /path/to/your/project
Create and activate virtual environment:
python3 -m venv env source env/bin/activate # On Windows: env\Scripts\activate
Install dependencies:
pip install -r requirements.txt # or with uv (recommended) uv pip install -r requirements.txt
Set up environment variables:
cp .env.example .env # Edit .env with your GLM API key from Z.AI
Add the server to Claude Code:
# Using uv (recommended) uv run mcp install -e . --name "GLM Vision Server" # Or manually add to Claude Desktop configuration: claude mcp add-json --scope user glm-vision '{ "type": "stdio", "command": "/path/to/your/project/env/bin/python", "args": ["/path/to/your/project/glm-vision.py"], "env": {"GLM_API_KEY": "your_api_key_here"} }'

Configuration

Set these environment variables in your .env file:

Variable	Description	Default
`GLM_API_KEY`	Your GLM API key from Z.AI	(required)
`GLM_API_BASE`	GLM API base URL	`https://api.z.ai/api/paas/v4`
`GLM_MODEL`	Model name to use	`glm-4.5v`

Usage

Available Tools

`glm-vision`

Analyze an image file using GLM-4.5V's vision capabilities. Supports both local files and URLs.

Parameters:

image_path (required): Local file path or URL of the image to analyze
prompt (required): What to ask about the image
temperature (optional): Response randomness (0.0-1.0, default: 0.7)
thinking (optional): Enable thinking mode to see model's reasoning process (default: false)
max_tokens (optional): Maximum tokens in response (max 64K, default: 2048)

Example:

Use the glm-vison tool with: - image_path: "/path/to/your/image.jpg" - prompt: "Describe what you see in this image"

Testing

Test the server using the MCP Inspector:

# With uv uv run python glm-vision.py # Or with python python glm-vision.py

Development

Running Tests

# Install development dependencies pip install -e ".[dev]" # Run tests pytest # Format code black . isort . # Type checking mypy glm-vision.py

Troubleshooting

API Key Issues: Make sure your GLM_API_KEY is correctly set in the environment
Connection Problems: Check your internet connection and API endpoint
Model Errors: Verify that the model name (GLM_MODEL) is correct and available

License

MIT License - see LICENSE file for details.

Contributing

Fork the repository
Create a feature branch
Make your changes
Add tests if applicable
Submit a pull request

Support

For issues related to the GLM API, contact Z.AI support. For MCP server issues, please create an issue in the repository.

This server cannot be installed

-

security - not tested

-

license - not tested

-

quality - not tested

How are these scores calculated?

Enables image analysis using GLM-4.5V's vision capabilities from Z.AI. Supports analyzing both local image files and URLs with customizable prompts and parameters.

GLM Vision Server