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Zhipu AI Image
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6 months ago
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3 months ago
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Documentation & install
Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.
Installation
Add the following to your MCP client configuration file.
Configuration
View docs{
"mcpServers": {
"lisy09-zhipu_image_mcp": {
"command": "python",
"args": [
"cogview_server.py"
],
"env": {
"ZHIPU_API_KEY": "your_api_key_here"
}
}
}
}You run a dedicated MCP server that uses the CogView4 model to generate images from text prompts. It supports multiple image sizes, automatically saves outputs locally, and exposes a simple MCP endpoint you can call from compatible clients to generate images on demand.
How to use
Start by launching the local MCP server, which runs a Python script named cogview_server.py. Once running, you can request image generation by calling the server’s available tool from your MCP client. The server accepts a text prompt in Chinese to guide image creation and selects from preset output sizes. Generated images are saved in the generated_images directory with a timestamped filename.
How to install
Prerequisites you need before installation are Python (3.8 or newer) and a working internet connection to install dependencies.
# 1) Clone the project
git clone https://github.com/lisy09/zhipu_image_mcp.git
cd zhipu_image_mcp
# 2) Install MCP dependencies via the MCP tooling (uv) if you have it installed, otherwise use pip as a fallback
uv sync
# If uv is not available, install dependencies with pip as a fallback
pip install -r requirements.txt
Additional configuration and usage notes
Before starting, set your API key for the image generation service. The server reads this key from the environment variable ZHIPU_API_KEY.
To run the server locally, use the following command. It starts the CogView4 MCP endpoint and enables image generation via the MCP client.
python cogview_server.py
Available tools
generate_cogview4_image
Generates an image from a text prompt. Accepts a mandatory prompt and an optional size (1024x1024, 768x768, 576x1024). The resulting image is saved to generated_images with a timestamped filename.