Multi-Agent Orchestration with MCP Protocol (Model Context Protocol)
Duration
3 Day
Level
Basic to Intermediate Level
Design and Tailor this course
As per your team needs
Overview
This 3-day program provides a structured introduction to Multi-Agent Orchestration using the Model Context Protocol (MCP). Participants will learn how MCP enables standardized communication between LLMs, tools, and external systems, allowing agents to dynamically discover capabilities, access contextual data, and execute tasks in interoperable environments.
The course progresses from foundational agentic AI concepts to designing and implementing multi-agent orchestration using MCP-compliant tools and services. Emphasis is placed on architecture design, protocol understanding, secure context sharing, scalability, and enterprise deployment patterns.
Hands-on labs guide participants through building MCP-connected agents, tool servers, and orchestrated multi-agent workflows.
Audience
- Generative AI Engineers
- AI/ML Engineers
- LLM Application Developers
- Platform Engineers
- Solution Architects
- Automation Engineers
Prerequisites
- Python programming knowledge
- Basic understanding of LLMs and prompt engineering
- Familiarity with APIs and JSON
- No prior MCP experience required
Curriculum
Production Architecture for MCP-Based Systems
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Service-based deployment model
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API gateway integration
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Containerized MCP servers
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Scaling orchestration services
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Observability and monitoring
Security & Governance
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Authentication and authorization
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Secure tool invocation
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Data privacy and context isolation
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Prompt injection mitigation
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Audit logging
Evaluation & Performance Optimization
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Agent success metrics
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Latency measurement
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Tool performance benchmarking
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Token usage optimization
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Cost control strategies
Advanced Topics (Basic to Intermediate Depth)
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Multi-agent negotiation patterns
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Human-in-the-loop workflows
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Hybrid orchestration (LangGraph + MCP)
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Distributed agent systems
Capstone Project: End-to-End MCP-Orchestrated System
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Define use case (research assistant or workflow automation)
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Design multi-agent architecture
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Implement MCP-connected tools
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Add monitoring and security controls
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Present architecture trade-offs and scalability plan
Upon completion, participants will be able to:
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Understand and implement the MCP protocol for tool integration
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Design multi-agent orchestration architectures
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Build interoperable AI systems using standardized tool interfaces
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Securely manage context exchange across agents
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Deploy scalable MCP-based agent systems
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Evaluate and optimize system performance and cost efficiency
Duration
3 Day
Level
Basic to Intermediate Level
Design and Tailor this course
As per your team needs
