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Tripo AI
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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": {
"pasie15-tripo-ai-mcp-server": {
"command": "tripo-ai-mcp-server",
"args": [],
"env": {
"TRIPO_API_SECRET": "YOUR_API_SECRET"
}
}
}
}You run the Tripo AI MCP Server to give AI assistants access to Tripo’s 3D generation capabilities. It lets you generate 3D models from text or images, animate models, apply styles, and track task progress, all through a safe, standardized MCP interface.
How to use
Start by launching the MCP server locally so clients can connect to it. The server exposes a set of tools that you can call from your MCP client to create and manipulate 3D content.
Common usage patterns span text-to-3D, image-to-3D, multiview-to-3D, and additional operations like animation and stylization. Ensure your MCP client is configured with your API secret so requests are authenticated.
How to install
Prerequisites: you need Node.js and npm installed on your system. Ensure you have a supported shell to run commands.
Install the MCP server globally so you can run it from any location.
npm install -g tripo-ai-mcp-server
Additional sections
Configuration is done via an API secret. You can set it in a .env file or pass it through an environment variable named TRIPO_API_SECRET.
Client configuration example for Claude Desktop shows how to run the MCP server as a local process and provide the API secret to the client.
{
"mcpServers": {
"tripo-ai": {
"command": "npx",
"args": [
"-y",
"tripo-ai-mcp-server"
],
"env": {
"TRIPO_API_SECRET": "your_api_secret_here"
}
}
}
}
To start the MCP server directly from the command line, run the following.
tripo-ai-mcp-server
Notes on security and usage
Protect your API secret. Do not share it in public tooling configurations or logs. If you need to rotate keys, update the secret in your environment and in any client configurations.
The server currently supports a set of tools for creating and transforming 3D content, with task status checks to monitor progress.
Available tools
text_to_3d
Create a 3D model from a text prompt.
image_to_3d
Create a 3D model from an image input.
multiview_to_3d
Create a 3D model from multiple viewpoint images.
get_task_status
Check the status of a previously submitted generation task.
upload_file
Upload a file manually to be used in generation tasks.
animate_model
Animate a rigged 3D model.
stylize_model
Apply a style to a 3D model.