multimodal agents course
pipStandardExposes multimodal AI agent capabilities for processing and understanding text, images, and audio. Provides tools for building agents that can handle multiple data types. Integrates with various multimodal models and APIs. Useful for developers creating AI agents that need to process and respond to diverse input types.
5281390Updated 1 month ago
Overview
Exposes multimodal AI agent capabilities for processing and understanding text, images, and audio. Provides tools for building agents that can handle multiple data types. Integrates with various multimodal models and APIs. Useful for developers creating AI agents that need to process and respond to diverse input types.
Installation
1Install the package
pip
pip install multimodal-agents-course2Add to Claude
Add this configuration to your claude_desktop_config.json:
claude_desktop_config.json
{
"mcpServers": {
"the-ai-merge-multimodal-agents-course-github": {
"command": "uvx",
"args": [
"pip install multimodal-agents-course"
]
}
}
}3Verify installation
Restart Claude Desktop, then ask:
"What tools do you have available from multimodal agents course?"
Prerequisites
- Python 3.10 or higher
- pip or uv package manager
- Claude Desktop or Claude API access
- API key for multimodal agents course
Configuration
API Key Required
This server requires an API key from multimodal agents course. Add it to your environment or config.
| Variable | Required | Description |
|---|---|---|
| MULTIMODAL_AGENTS_COURSE_API_KEY | Yes | Your multimodal agents course API key |
Usage Examples
List Resources
"What resources are available in multimodal agents course?"
Claude will query available resources and return a list of what you can access.
Get Details
"Show me details about [specific item] in multimodal agents course"
Claude will fetch and display detailed information about the requested item.
Create New
"Create a new [item] in multimodal agents course with [details]"
Claude will use the appropriate tool to create the resource and confirm success.
Works with multimodal agents course
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