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MCP and A2A in Python: The Agent Protocol Course

Ship production MCP servers, A2A clients, and multi-agent integrations in Python. Verified against current SDKs.

Agent integrations are fragmenting faster than teams can keep up. Every LLM vendor ships a new tool format, every framework invents its own agent contract, and production code rots in months. Two emerging standards fix this: the Model Context Protocol (MCP) and the Agent-to-Agent (A2A) protocol. This course teaches you how to use both with working Python code.

What you’ll learn

Course Content

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Agent integrations are fragmenting faster than teams can keep up. Every LLM vendor ships a new tool format, every framework invents its own agent contract, and production code rots in months. Two emerging standards fix this: the Model Context Protocol (MCP) and the Agent-to-Agent (A2A) protocol. This course teaches you how to use both with working Python code.

Every lecture pairs a concise video briefing with a long-form PDF extension you can inspect and return to: protocol diagrams, sequence flows, and Python reference implementations. No filler, no marketing slides. You read the spec, build the server, and connect a client.

You will implement a FastMCP server with resources, tools, and prompts, then consume it from an MCP client using stdio and Streamable HTTP transports. You will build A2A servers and clients using the a2a-sdk, model the agent card, and walk through the task lifecycle. You will design synchronous integrations with proper error handling and asynchronous, event-driven workflows with streaming and callbacks.

By the final section, you combine MCP and A2A in a single end-to-end project: an orchestrator agent that exposes MCP tools, consumes a remote A2A worker, and handles retries and timeouts cleanly. You leave with a reference architecture you can adapt to your codebase on Monday.

Enroll now and move from protocol confusion to protocol fluency. The specs are stabilizing fast. Being the engineer who already knows them is the advantage.

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