iflow-mcp_mcp-server-glm-vision

# 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 1. **Clone or create the project directory:** ```bash cd /path/to/your/project ``` 2. **Create and activate virtual environment:** ```bash python3 -m venv env source env/bin/activate # On Windows: env\Scripts\activate ``` 3. **Install dependencies:** ```bash pip install -r requirements.txt # or with uv (recommended) uv pip install -r requirements.txt ``` 4. **Set up environment variables:** ```bash cp .env.example .env # Edit .env with your GLM API key from Z.AI ``` 5. **Add the server to Claude Code:** ```bash # 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 abo…