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Skill track

MCP courses

MCP (Model Context Protocol) is the standard for giving LLMs access to your tools and data without rewriting integrations for every new model. Think of it as the USB-C moment for AI tooling. One protocol, any client, any server.

Curated by Param Harrison

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These courses walk through both sides: building MCP servers that expose your tools, and MCP clients that consume them. Real examples include a code-review bot, a repo assistant, and patterns for production deployment.

Showing 3 of 3 courses

QKV

GenAI Masterclass: Go from Zero to One

6 hands-on projects. 6 core AI skills. Zero fluff.

NoobsFree
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clientMCPserver

MCP Fundamentals for Engineers

Build MCP servers and clients from scratch. No more glue code.

BeginnerFree
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Building MCP servers for GitHub PR review

Build an MCP server that reviews GitHub pull requests end to end.

IntermediatePro
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Common questions

MCP: quick answers

  • What is MCP exactly?

    A protocol that lets any LLM client (Claude Desktop, ChatGPT, your custom agent) talk to any tool server using a common message shape. Instead of writing one-off integrations for every model, you write one MCP server and all clients can use it.

  • Do I need MCP if I use OpenAI or Claude function calling?

    For a single client, no. Direct function calling works fine. MCP pays off when you want the same tools available across Claude Desktop, Cursor, ChatGPT, and your own agents, or when tools need to live in a separate process.

  • Python or TypeScript for MCP servers?

    Both SDKs are production-ready. Python via FastMCP, TypeScript via the official SDK. The courses use Python because that’s where most backends live, but the protocol is the same.

  • How does authentication work?

    MCP itself doesn’t specify auth. It’s up to the transport. For remote servers, OAuth or bearer tokens via HTTP headers. For local servers, OS-level trust. The PR review server course covers a real auth setup.

  • How does MCP relate to agents?

    MCP is how an agent discovers and calls tools. Agents bring the reasoning loop; MCP brings the tool interface. The MCP PR Review Server course combines both.

Related paths

AI EngineerAI AgentsPythonFastAPI
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