The growing landscape of AI agent development is overloaded with acronyms: MCP, A2A, UCP, AP2, A2UI, and AG-UI, just to name a few. If you’ve ever looked at this list of protocols and felt like you were staring at a wall of competing standards, you are not alone. To help you understand their value, we are going to demonstrate what each one does to save you from writing and maintaining custom integration code for every single tool, API, and frontend component your agent touches
In Pulse we have recently featured some excellent examples of agentic integration into Google Workspace, in particular, Pierrick Voulet’s insightful posts on extending Chat apps with Universal Actions provide a great template for building intelligent assistants. For those following Pierrick on LinkedIn you’ll know these are just the tip of the iceberg.
With users increasingly expecting these intelligent assistants to communicate seamlessly across their everyday tools, knowing the right standards to connect different systems becomes a significant challenge. Fortunately, the Google Developers Blog has published a comprehensive guide to help navigate this exact problem.
In a recent post there is an overview of the growing list of acronyms associated with AI agent development. The post breaks down six main protocols:
Model Context Protocol or MCP: This standardizes connection patterns for servers. Instead of writing custom API requests for every service, your agent discovers tools automatically.
Agent2Agent Protocol or A2A: This standardizes how remote agents discover and communicate with each other using well-known URLs.
Universal Commerce Protocol or UCP: This modularizes the shopping lifecycle into strongly typed schemas that remain consistent across any underlying transport.
Agent Payments Protocol or AP2: This adds cryptographic proof of authorization to checkout flows to enforce configurable guardrails on transactions.
Agent-to-User Interface Protocol or A2UI: This lets the agent dynamically compose novel layouts from a fixed catalog of safe component primitives.
Agent-User Interaction Protocol or AG-UI: This acts as middleware that translates raw framework events into a standardized stream for the frontend.
To illustrate these concepts, the guide walks through building a multi-step supply chain agent using the Agent Development Kit. The scenario starts with a bare large language model and progressively adds protocols until the agent can check inventory, get quotes, place orders, authorize payments, and render interactive dashboards.
Adopting standard protocols is only half the equation, and how effectively you apply them shouldn’t be overlooked. As an example, Richard Seroter recently highlighted this in his analysis of agent token consumption. He discovered that simply attaching an MCP to an agent often leads to excessive planning iterations and high token costs. By pairing an MCP with a highly focused “Skill”, a structured set of instructions that guides the tool’s application, developers can drastically cut down on wasted turns. In one test, combining an MCP with a specific skill resulted in an 87% reduction in token usage compared to letting the agent figure out the tool on its own.
For Google Workspace developers building complex integrations, it’s important not to just be aware of the emerging protocols, but also the best practices for implementing them. Giving your agent a connection is a great start; teaching it the specific skill to use that connection efficiently is essential.
