Model Context Protocol (MCP)

Live Online (VILT) & Classroom Corporate Training Course

Understand and implement the Model Context Protocol (MCP) for connecting AI applications and agents with external tools, resources and systems through a standardized interface - architecture, clients, servers, resources, tools, prompts, discovery, security and production best practices.

Expert-Led VILT & Classroom 8 Hours Level: Intermediate - Advanced Certificate of Completion
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Overview

Understand and implement the Model Context Protocol (MCP) for connecting AI applications and agents with external tools, resources and systems through a standardized interface - architecture, clients, servers, resources, tools, prompts, discovery, security and production best practices.

What You Will Learn

By the end of this course, learners will be able to:

  • Explain the purpose, architecture and core concepts of Model Context Protocol.
  • Understand the roles of MCP clients, servers, resources, tools and prompts.
  • Discover and interact with MCP capabilities programmatically.
  • Develop an MCP server exposing custom tools and resources.
  • Connect MCP servers to APIs, databases, files and external systems.
  • Integrate MCP with LLM-powered applications and AI agents.
  • Apply authentication, authorization, validation and least-privilege security principles.
  • Handle MCP errors, tool failures and integration issues.
  • Build and test an MCP server using a practical real-world use case.
  • Connect an AI agent to an MCP server and execute multi-step tool workflows.

Prerequisites

Basic Python programming, familiarity with LLMs, APIs, AI agents and function/tool calling is recommended.

Course Outline

  • What is Model Context Protocol (MCP)?
  • Why MCP?
  • Problems MCP Solves
  • MCP vs Traditional API and Tool Integration
  • MCP Architecture Overview
  • Core MCP Components
  • Communication and Message Flow
  • MCP Capabilities and Lifecycle
  • MCP Use Cases
  • Benefits and Limitations of MCP

  • What is an MCP Client?
  • What is an MCP Server?
  • Client-Server Communication
  • MCP Server Capabilities
  • Capability Negotiation
  • MCP Resources, Tools and Prompts
  • Server Discovery and Connection
  • Request and Response Lifecycle
  • Managing Multiple MCP Servers
  • MCP Integration Patterns

  • MCP Resources Fundamentals
  • Resource URIs and Resource Content
  • Dynamic and Static Resources
  • MCP Tools Fundamentals
  • Tool Definitions and Input Schemas
  • Tool Invocation and Tool Results
  • MCP Prompts
  • Prompt Templates and Arguments
  • Tool and Resource Discovery
  • Listing and Selecting Available Capabilities
  • Handling Tool and Resource Errors

  • MCP Server Development Fundamentals
  • Setting Up the Development Environment
  • Server Initialization and Lifecycle
  • Implementing MCP Tools
  • Implementing MCP Resources
  • Implementing MCP Prompts
  • Defining Input and Output Schemas
  • Handling Requests and Responses
  • Connecting Server Tools to External APIs
  • Connecting to Databases and Files
  • Error Handling and Validation
  • Testing and Debugging an MCP Server

  • MCP in LLM and Agent Architectures
  • MCP Client Integration
  • Connecting AI Models to MCP Servers
  • Tool Discovery by AI Agents
  • Selecting and Invoking MCP Tools
  • Connecting External APIs
  • Database and Knowledge-System Integration
  • File and Enterprise-System Integration
  • Returning Tool Results to the Model
  • Designing Reliable MCP Integrations

  • MCP Security Fundamentals
  • Authentication Concepts
  • Authorization and Access Control
  • Tool Permission Management
  • Input Validation and Output Validation
  • Secure Handling of Credentials and Secrets
  • Preventing Unauthorized Tool Execution
  • Sandboxing and Least-Privilege Principles
  • Logging, Monitoring and Auditing
  • MCP Best Practices for Production

  • Define the MCP Server Use Case
  • Design the Server Architecture
  • Set Up the MCP Development Environment
  • Create the MCP Server
  • Implement Custom Tools
  • Define Tool Input and Output Schemas
  • Add MCP Resources
  • Add Reusable MCP Prompts
  • Implement External API or Database Integration
  • Add Validation and Error Handling
  • Test Tool Discovery and Invocation
  • Debug and Optimize the MCP Server

  • Define the Agent Use Case
  • Design the Agent-MCP Architecture
  • Configure the MCP Client
  • Connect the AI Agent to the MCP Server
  • Discover Available MCP Tools
  • Enable Agent Tool Selection
  • Execute MCP Tools from the Agent
  • Process and Validate Tool Results
  • Implement Multi-Step Agent Workflows
  • Add Error Handling and Fallbacks
  • Apply Security and Permission Controls
  • Test the Complete Agent-MCP Workflow
  • Evaluate Reliability and Performance
  • Final Demonstration and Production Readiness Review

Available Training Modes

Pick the format that fits your team.

Same authorised curriculum, same trainers, same hands-on cloud labs — delivered the way that works for you.

Live Online (VILT)

Real-time instructor-led sessions over Zoom or Teams. Same classroom, different time zones.

Most popular

Classroom

Face-to-face training delivered at your office, our Bengaluru centre, or any partner venue worldwide.

Onsite

Self-Paced

Recorded sessions plus 24/7 access to cloud labs and assessments. Learn at the pace that works for each engineer.

On-demand

Blended

Live workshops with self-paced reinforcement and project-based labs. Best for hybrid teams across regions.

Hybrid teams
All modes include: hands-on cloud labs, recordings, assessments, certificate of completion. Talk to a solutions advisor →

Our Training Process

How a course becomes measurable skill.

One contract, five steps, zero handoffs. From discovery to deployment, the same Synergific team owns the outcome — not a chain of vendors.

5 Steps from your scoping call to certified, productive engineers.
01

Discover & set goals

We start with a scoping call to understand your team's current skill level, target outcomes, deadlines, and certification needs — then translate that into a measurable success plan with named owners on both sides.

02

Curate the right path

We map the optimal learning path — instructor-led, self-paced, or blended — with hands-on cloud labs, prerequisite refreshers, and certification vouchers built in. No filler modules, no padded curriculum.

03

Deliver hands-on training

Authorised trainers run live sessions backed by 24/7 cloud labs and real-world projects. Theory and practice on the same day — learners stop forgetting concepts before they get to apply them.

04

Assess & mentor

Continuous skill checks, mock exams, and 1:1 mentoring keep the program honest. If anyone falls behind, we course-correct in-flight — you'll never find out at the end that two engineers couldn't keep up.

05

Certify & apply on the job

Voucher-backed certification, post-training office hours, and 30-day reinforcement so skills land on real work — not just on the exam scorecard. Success measured after the course ends, not before.

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