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.