MCP Tutorial
Learn MCP for Real AI Integrations
Learn Model Context Protocol (MCP) from first principles through architecture, transports, capability design, server implementation, client integration, security, debugging, and production deployment.
17Topics
23+Examples
FreeAlways
About MCP
Learn Model Context Protocol (MCP) from first principles through architecture, transports, capability design, server implementation, client integration, security, debugging, and production deployment.
Prerequisites
Basic TypeScript or Python, JSON, HTTP, process execution, and API security concepts will help you implement the examples.
Who This Is For
Developers and architects building reusable AI integrations for desktop apps, IDEs, internal copilots, and hosted services.
What You Will Learn
Protocol lifecycle, capabilities, tools, resources, prompts, sampling, elicitation, tasks, transports, authorization, and operations.
Tools Needed
A code editor, Node.js or Python, an MCP SDK, MCP Inspector, and an MCP-capable host for integration testing.
Tutorial Topics
Follow the lessons in order, or jump straight into the topic you need.
1. MCP Foundations
Lesson
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Open this lesson in the MCP tutorial path.
3. Hosts, Clients & Servers
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4. Tools, Resources & Prompts
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Open this lesson in the MCP tutorial path.
9. Roots & Context
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10. Sampling, Elicitation & Tasks
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Open this lesson in the MCP tutorial path.
12. Build an MCP Server
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13. Client Integration
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14. Debugging & Inspector
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15. Security & Production
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Why Learn MCP?
- Build integrations that can work across multiple compatible AI hosts.
- Design narrow, typed capabilities instead of exposing raw backend APIs.
- Understand bidirectional client and server features, not only tool calls.
- Apply transport, authorization, consent, and audit controls correctly.
- Debug and operate MCP servers with protocol-level visibility.