Edureka

CrewAI Tools, MCP, and Agentic RAG

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Edureka

CrewAI Tools, MCP, and Agentic RAG

Edureka

Instructor: Edureka

Included with Coursera Plus

Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Define how tools, memory, MCP, and Agentic RAG enable intelligent and scalable multi-agent systems

  • Apply CrewAI tools, memory systems, and retrieval techniques to build structured and context-aware agent workflows

  • Analyze agent behavior, workflow design, and knowledge retrieval strategies to improve accuracy and system performance

  • Design secure, scalable multi-agent systems integrating tools, memory, MCP, and Agentic RAG for real-world applications

Details to know

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Recently updated!

April 2026

Assessments

14 assignments¹

AI Graded see disclaimer
Taught in English

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Build your subject-matter expertise

This course is part of the Mastering CrewAI for Multi Agent Systems Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 4 modules in this course

Learn how tools extend agent capabilities beyond text generation in CrewAI. Explore built-in tools for tasks such as web research, data extraction, and reporting, and understand how agents use them within structured workflows. Gain hands-on experience building custom tools and designing multi-step workflows using tool chaining and orchestration. Develop practical skills to create agents that interact with external systems and execute real-world tasks.

What's included

14 videos5 readings4 assignments

Discover how intelligent agents store, retrieve, and use information through memory systems in CrewAI. Learn how to configure memory for persistence, relevance, and role-specific behavior, enabling agents to maintain context across interactions. Explore Agentic RAG and how agents use external knowledge sources to generate grounded and accurate responses. Develop skills to design context-aware and knowledge-driven agent systems.

What's included

10 videos4 readings4 assignments

Learn how to extend agents using the Model Context Protocol (MCP) for structured and scalable communication. Explore how agents discover and interact with tools through MCP servers and integrate MCP into CrewAI workflows. Gain hands-on experience designing secure workflows with role-based access control and token validation. Develop the ability to build flexible and production-ready agent systems with controlled tool access.

What's included

12 videos4 readings4 assignments

Consolidate your learning across tools, memory, MCP, and Agentic RAG. Apply your skills in a hands-on project by building a knowledge-driven agent system that integrates tool usage, memory, and retrieval. Complete a graded assessment to demonstrate your ability to design and implement scalable agent workflows. Reflect on your progress and prepare for more advanced multi-agent system design.

What's included

1 video1 reading2 assignments1 discussion prompt

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructor

Edureka
Edureka
170 Courses151,746 learners

Offered by

Edureka

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¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.