This course teaches beginners how to use CrewAI with FastMCP server access through step-by-step programming examples.
{
"mcpServers": {
"crewai-mcp-course": {
"command": "<see-readme>",
"args": []
}
}
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This course teaches beginners how to use CrewAI with FastMCP server access through step-by-step programming examples.
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Last commit 260 days ago. 16 stars.
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Transport: stdio. Works with Claude Desktop, Cursor, Claude Code, and most MCP clients.
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This course teaches beginners how to use CrewAI with FastMCP server access through step-by-step programming examples.
This course is designed for beginner developers with basic Python knowledge who want to learn how to integrate CrewAI agents with FastMCP servers. The course covers fundamental concepts, practical implementation, and advanced patterns for building intelligent agent workflows.
graph TD
A[Install Packages] --> B[Set Environment Variables]
B --> C[Create CrewAI Agent]
C --> D[Execute Task]
graph TD
A[Create FastMCP Tool] --> B[Configure Authentication]
B --> C[Create Agent with Tool]
C --> D[Execute Task with MCP Data]
D --> E[Handle Response]
graph TD
A[Researcher Agent] -->|Query| B(FastMCP Server)
B -->|Return Data| A
A -->|Share Findings| C[Writer Agent]
C -->|Create Report| D[Reviewer Agent]
D -->|Provide Feedback| C
C -->|Final Report| E[Output]
pip install -r requirements.txt
export FASTMCP_URL=http://your-fastmcp-server-url:port
export FASTMCP_API_KEY=your-api-key
python lesson1_setup.py
python lesson2_mcp_integration.py
python lesson3_advanced_patterns.py
Each lesson includes:
After completing this course, you should be able to: