
Identify prerequisites: junior-level python, basic git and shell use, and a basic understanding of web servers and http endpoints; optional familiarity with LLMs and agent orchestration.
Meet Markus, a seasoned backend developer with a data science background, and learn his practical, theory-first teaching style for the Agent2Agent (A2A) protocol, followed by hands-on exploration of A2A.
Explore why diverse agents can't talk due to different frameworks and languages, and how A2A provides a common protocol for discovery, task handoff, and secure orchestration.
Master the agent-to-agent protocol (A2A), an open standard enabling independent AI agents to discover each other, exchange messages, track tasks, and return results without revealing internals.
Compare MCP and A2A: MCP connects an agent to tools and data, while A2A connects to other autonomous agents; use both to enable tool access and peer collaboration.
Map the A2A protocol by pairing a client with a server agent, using the agent card for discovery, and exchanging messages, tasks, parts, and artifacts to complete work.
Discover the three-layer A2A architecture, with data model, operations, and bindings, and see how REST, JSON RPC, and gRPC carry the same actions.
Repository Link: https://github.com/Coding-Crashkurse/A2A-Udemy-Course
Launch your first A2A server and client with an echo executor, processing input via request context and event queue, then explore agent card and routes.
Build a reusable agent client that reads the agent card, selects the appropriate binding (JSON-RPC, REST, or gRPC), and talks to the agent via a factory-created connection.
Configure O2 transport discovery with share.py’s echo executor to build three agent cards and an in-memory task store, and bind jsonRPC, http, and gRPC.
Explore the task concept at the heart of A2A and track its lifecycle states. Distinguish artifacts and status messages, and compare simple messages with time-consuming tasks.
Explore the task lifecycle in an agent-to-agent workflow, evolving a task from submitted to working and finally to completed, rejected, or failed, with updates and artifacts.
Mastering Agent2Agent Protocol (A2A): practical guide explains request configuration, including return immediately, history length, accepted output modes, and task push notifications, with blocking versus fire-and-forget and polling or webhook patterns.
Learn to exchange structured json via A2A data parts, using a protobuf value to send and receive data parts, and return a tickets.json artifact after filtering tickets by status.
Explore file exchange with A2A by comparing sending raw bytes in messages versus using URLs. Learn which approach fits different scenarios and understand the security considerations of URL references.
Master the file exchange in the A2A protocol by sending raw bytes as file parts and retrieving the updated content via a download URL.
Learn how to send file references via uri using a local file server, validate fetch URLs to mitigate ssrf risks, and implement a secure client-server workflow for uri-based file delivery.
Learn how polling enables long-running tasks by returning a task ID and polling until completion, balancing reliability behind firewalls with latency and wasted requests.
Learn how to implement polling for an A2A task: create a task from a client message, update progress, and poll the get task endpoint until completion to retrieve the artifact.
Learn how streaming via server-sent events (SSE) solves long-running tasks by delivering low-latency updates over a kept-open http connection, with a resubscribe mechanism in the A2A SDK.
Enable streaming via the A2A SDK to receive live updates, including task opening snapshot, status updates, and artifact payload, by configuring streaming true on server and client, and handle reconnections.
Resubscribe reconnects to an ongoing streaming task after an interruption by reattaching via the task ID, allowing continued SSE updates, artifacts, and final events, with caveats about backfill.
Master push notifications as an update, where the agent posts updates to your webhook via http post after the client registers a callback url and secret token to verify updates.
Demonstrate push notifications in the A2A workflow by wiring an in-memory push config store and a base sender to push task updates to registered webhooks.
Understand how tasks move from submitted to terminal states, enter an input-required pause, and resume with the same TaskId to enable true multi-turn conversations in the Agent2Agent protocol.
Coordinate multi-turn conversations by creating new tasks from user messages, updating task states to input required and then working toward completion, while the client uses task IDs and context IDs.
Learn how a client, often a software component, talks to an agent via the 808 protocol and uses ListTask to view many tasks across states with paging for dashboards.
Simulate a task flow with a server queuing user input, marking tasks as completed or failed in memory, while a client sends 10 messages and operator lists tasks with filters.
Mastering the A2A Protocol (Agent2Agent) is your practical guide to building interoperable, secure, and production-ready AI agents that can discover, talk to, and delegate work to one another.
This course walks you through every step, from your very first simple request-response A2A server to a full multi-agent orchestrator that routes tasks, reads AgentCards, and delegates across specialized agents.
You'll learn how the A2A protocol lets agents built on different frameworks and by different vendors collaborate as peers through messages, tasks, streaming, and secure authentication. A2A is an open standard (originally introduced by Google, now under the Linux Foundation) that complements MCP: where MCP connects an agent to its tools and data, A2A connects agents to other agents. With a strong focus on hands-on development (every concept ships with a working Python client and server), this course prepares you to build agent systems that are ready for real-world use.
Course Highlights
A2A Fundamentals: Understand why agents need a common protocol, what A2A actually is, how it differs from and complements MCP, and the three core architecture layers.
Messages, Tasks & Transport: Build your first A2A server, master bindings and transport discovery, and work through the complete task lifecycle from creation to completion.
Structured Data & File Exchange: Move from plain text to structured Data Parts, handle configuration options, and send files both as raw bytes and via URI references with a dedicated web server.
Long-Running Tasks (Polling & Streaming): Handle long-running work with polling, stream results in real time via SSE, and use resubscribe to reconnect to a task after dropping off.
Push Notifications: Notify clients asynchronously when tasks finish, even after they've disconnected.
Multi-Turn Conversations & Task Management: Run multi-turn conversations via input-required, list multiple tasks at once, and cancel running tasks cleanly.
Security with OAuth 2.0 & Auth0: Understand why agents must be secured, set up Auth0, and protect your A2A application end-to-end with the OAuth 2.0 workflow.
A2A Orchestrator (Capstone): Combine everything into a real orchestrator that routes requests, reads AgentCards, and delegates across specialized agents.
Advanced Topics: Go further with versioning, extended AgentCards, and protocol extensions.
By the end of this course, you'll not only understand the theory behind A2A but also have the skills to build, secure, and deploy interoperable agents in modern AI workflows.
Whether you're a developer exploring multi-agent systems or an engineer connecting agents across frameworks and platforms, this course gives you the practical tools to take your AI agents to the next level.
Let's build the next generation of collaborative, agent-to-agent systems :-)