AI Agents Fastmcp
Learn about AI agents and build a FastMCP agent with Claude integration
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Documentation
AI Agents & FastMCP with Claude Integration
This repository contains educational materials and implementation code for understanding AI agents and building a FastMCP agent with Claude integration.
Sessions Covered
-
Introduction to AI Agents: Theory & Architecture (Mar 16)
- Fundamentals of AI agents
- Agent design principles and patterns
- Decision-making frameworks
- Agent environments and capabilities
-
Building AI Agents: FastMCP with Claude Integration (Mar 30)
- FastMCP architecture and components
- Claude AI integration techniques
- Autonomous task execution implementation
- Complex reasoning and planning capabilities
Project Structure
/theory /diagrams /concepts /examples /implementation /fastmcp-core /claude-integration /demos /resources /papers /tutorials /references
Getting Started
- Clone this repository:
git clone https://github.com/BenjiCoder24/ai-agents-fastmcp.git
- Set up your environment:
cd ai-agents-fastmcp
pip install -r requirements.txt
- Configure your API keys:
ANTHROPIC_API_KEY=your_claude_api_key_here
- Run the example agent:
python examples/basic_agent.py
Key Concepts Covered
- Agent architectures (reactive, deliberative, hybrid)
- Agent environments and constraints
- FastMCP (Fast Multi-Context Planning) methodology
- Claude API integration for reasoning tasks
- Task decomposition and planning
- Autonomous execution frameworks
- Evaluation metrics for agent performance
Technologies Used
- Python 3.9+
- Anthropic Claude API
- FastMCP framework
- Cursor IDE
- Visualization tools for agent behavior
Resources
License
This project is licensed under the MIT License - see the LICENSE file for details.
