Agentic AI with Agno and MCP Crash Course Crash Course
Unlock the power of Agentic AI with this focused, hands-on course designed to teach you how to build intelligent financial agents using the Agno Agentic Framework and the MCP (Message, Chain, Plan) Protocol. Whether you’re an AI enthusiast, developer, or a financial tech innovator, this course will help you grasp the next evolution of AI workflows through practical projects.
What you’ll learn
- Learn how to use the MCP (Message, Chain, Plan) protocol to build structured, intelligent agents..
- Gain hands-on experience developing financial agents that can analyze data and automate real-world tasks..
- Understand how to integrate memory into your agents so they can recall past interactions and make informed decisions..
- Using the Agno Playground, you’ll simulate and visualize agent workflows in an interactive environment..
- Create multi-agent systems where agents collaborate, delegate tasks, and solve problems together..
Course Content
- Introduction –> 7 lectures • 14min.
- Project Agno Financial assistant –> 1 lecture • 5min.
- Agno memory Agent –> 4 lectures • 17min.
- Agno Multi Agent –> 4 lectures • 19min.
- Agno Playground –> 4 lectures • 13min.
- MCP Protocol Overview –> 3 lectures • 15min.
- Project: Agno Agent with MCP –> 5 lectures • 25min.
- Appendix- Python –> 36 lectures • 2hr 59min.
Requirements
Unlock the power of Agentic AI with this focused, hands-on course designed to teach you how to build intelligent financial agents using the Agno Agentic Framework and the MCP (Message, Chain, Plan) Protocol. Whether you’re an AI enthusiast, developer, or a financial tech innovator, this course will help you grasp the next evolution of AI workflows through practical projects.
You’ll dive into how Agno simplifies the development of autonomous, goal-driven agents using structured planning and communication patterns. Learn to design financial agents that can analyze market data, execute tasks, and retain knowledge using Memory Agents. Explore the Agno Playground, a visual environment to test and simulate agents with dynamic prompts and task flows.
The course emphasizes multi-agent collaboration where agents communicate and coordinate as teams to solve complex problems. Using real-world financial use cases, you’ll create agents that not only act independently but also plan, reflect, and delegate in multi-agent environments.
What you’ll build:
- A smart Financial Analyst Agent using Agno & MCP
- A Memory-augmented agent capable of recall and reasoning
- A Multi-Agent system where agents collaborate on financial tasks
- Use of Agno Playground to simulate and visualize workflows
No prior experience in agent frameworks is required—just a basic understanding of Python and AI concepts.
Start your journey into the world of Agentic AI today and build systems that think, plan, and act—autonomously.