Original article by @BlazingKevin_, the Researcher at Movemaker

Google's recently released AP2 protocol defines the underlying rules for payments and transactions in the upcoming agent economy. Its core mission is to complete the final piece of the puzzle—value settlement—between "AI analysis" (based on MPC) and "agent execution" (based on A2A). It aims to standardize payment processes for AI agents and formalize their interaction rules, ultimately fostering AI agents capable of autonomously completing commercial activities on behalf of users.

AP 2's primary application scenarios target core areas of the traditional internet, such as e-commerce and subscription services. This means its design aims to address the challenge of securely delegating payment authorization from humans to AI within existing business frameworks. This will directly impact the direction of e-commerce operations, freeing users from the need to click "buy" or "subscribe" to instead delegate intent and set rules to AI agents.

It's precisely based on this logic that we need to more carefully assess AP2's impact on the crypto industry. It wasn't designed for Web 3 native scenarios, but rather to incorporate crypto payments (especially stablecoins) as an optional, integrated payment option within its broader framework. Therefore, rather than saying AP2 will trigger an explosion in AI, it's more accurate to say it provides an interface for crypto assets to enter mainstream AI applications.

Understanding AP2's pre-protocols: MCP and A2A

AP2 is built on the development paths of two predecessor protocols: MCP and A2A. Understanding the nature and limitations of these two protocols is key to understanding the true purpose of AP2. MCP addresses the connection between AI and tools, while A2A seeks to address collaboration between AIs.

What is MCP? Let AI truly touch the real world

Large language models (such as Gemini and GPT) are essentially "super brains" isolated from the real world. They possess vast amounts of static knowledge, but lack access to real-time information and cannot directly operate any external software. For example, a user might send a request like "Book me a flight to Osaka tomorrow" and it wouldn't be able to complete it because it lacks the ability to interact with booking websites.

The Model Context Protocol (MCP) was developed to address the problem of how AI communicates with the external environment. MCP defines a standardized communication format, enabling AI to send requests to external tools (such as databases and APIs) and receive responses. Think of it as installing a telephone in this "secret room brain."

The MCP (Model Context Protocol) is the "standard intercom system" created to break this secret room.

Driven by industry giants like Anthropic, it aims to address the problem of standardized AI interaction with external data and tools (such as databases, software, and blockchains). Through this "intercom," AI models can issue requests to the outside world using a standard language. The MCP system then accurately transmits these requests to the corresponding external tools (such as weather APIs and ticket booking website APIs). Once the tools complete the request, they return the results to the AI in a standardized format.

However, analyzing the current MCP implementation, we will find that it is more like an "internal phone" that can only dial a few preset numbers.

Currently, AI's ability to call external tools is highly dependent on the platform's vertical integration. For example, when Gemini searches, it defaults to and exclusively calls Google Search; its code execution also runs within the platform's own sandbox environment. This model has direct impacts on users and developers:

• For users : The upper limit of AI capabilities is locked in by the platform. Users cannot choose third-party tools they consider superior (for example, using Perplexity for AI search or accessing specific financial data APIs). As a result, the practicality of AI is greatly limited, and the user experience is bound to the platform's ecosystem.
• For developers , this creates a de facto market barrier. Even if a developer creates an AI application in a specific field that far surpasses the platform's native tools, it cannot be fairly discovered and accessed by mainstream AI agents. Innovation is stifled, and market competition is confined to a closed, platform-dominated collaborative system.

A2A: From "Internal Phone" to "Public Yellow Pages"

If MCP gives AI the "hands and feet" to operate tools, then the A2A (Agent-to-Agent) protocol allows independent AI agents to learn how to communicate and collaborate. Built on MCP, it defines a set of common rules that enable independent AI agents developed by different companies and developers to discover and understand each other's capabilities, and collaborate to complete complex tasks that would be beyond the capabilities of a single agent.

The significance of A2A lies in upgrading MCP's task processing model from "single-soldier operation" to "project subcontracting." For example, when a user requests a complex request like "planning a beach party in Hawaii next month," within the closed system of MCP alone, individual agents can only clumsily access the limited tools allowed by the platform one by one.

But in the A2A concept, individual agents can act as "contractors." They break down tasks, post them on the A2A network, and seek out professional "travel agents," "catering agents," and "event planning agents" to collaborate on the tasks. This paradigm shift will have profound implications:

• For users : The capabilities of AI agents will increase exponentially. Users can confidently delegate extremely complex, cross-domain tasks because AI is no longer a simple tool operator, but a resource coordinator.
• For the industry : A2A aims to create an open, interoperable agent service marketplace. It addresses three core issues: discovery (establishing a mechanism similar to an agent app store), understanding (a standardized description language for agent capabilities), and collaboration (standardizing the process of task allocation and progress synchronization). Once this system matures, any standard-compliant agent developer will be able to register their services and be fairly selected by the market.

AP2's core mechanism: establishing a trust and authorization framework for agent transactions

MCP and A2A protocols solve the problems of "what agents can do" and "how to collaborate", but this immediately leads to a more difficult business problem: when agents begin to independently perform operations involving funds, who will be responsible for the legality and consequences of these actions?

The risk control logic of traditional online payment systems is based on a fundamental premise: a human user actively and in real time performing transactions in front of a screen. Any non-human, automated payment request is labeled high-risk by the existing financial system. This is the most fundamental obstacle to the development of the agent economy. Specifically, an AI-initiated transaction request raises three unanswerable questions for merchants and payment networks:

1. Proof of authorization : How to confirm that the user has truly authorized the AI to conduct this transaction?
2. Intent fidelity : Does the AI's specific request (e.g., purchase quantity, price) accurately reflect the user's true intent, especially when the user is not monitoring the request in real time?
3. Liability : If a transaction goes wrong, who is responsible for the losses?

Google's AP2 protocol was designed to systematically answer these three questions. AP2 aims to establish an open, standardized authorization and trust communication protocol between users, AI agents, and merchants.

The core technology of AP 2 is a dual authorization mechanism:

1. Real-time authorization (Cart Mandate)

This mechanism is familiar to credit card users. When you use a credit card to pay on a website, your phone will pop up an authorization window. This is what AP 2 does.

After completing preliminary work such as product research and price comparison, the agent generates a "shopping cart" containing all transaction details and presents it to the user. The transaction must wait for the user to review and sign before execution.

Impact Analysis : Real-time authorization is an early form of agent-based payment. It lowers the barrier to entry for users but does not fully leverage the autonomy of agents. Its primary value lies in optimizing the pre-transaction decision-making process, but the final "finishing touch" still requires human intervention.

2. Intent Mandate

This is the revolutionary aspect of AP 2. Users can pre-set complex, conditional orders. For example, "Only if the price of the Tesla Model Y drops by more than 20,000 yuan, automatically execute the purchase process, using funds from Account A. If Account A is insufficient, use Account B."

To make this “forward delegation” trustworthy and secure, the implementation logic of AP 2 is based on Verifiable Credentials (VCs):

• The user's complex entrustment conditions will be compiled into a tamper-proof digital "transaction contract" (VC) that is encrypted and signed by the user.
• At every key step in performing a task, the AI Agent needs to present this "contract" to prove the legality of its actions.
• All execution links will also generate corresponding VC records to ensure the auditability of the entire process.

For merchants and clearing networks (such as Visa) , they receive a "transaction contract" with the user's cryptographic signature, clearly defining the scope and conditions of authorization. By verifying this contract, they can gain sufficient confidence to confirm the legitimacy of the transaction, significantly reducing fraud risk and compliance costs.

For users : This makes true "7 x 24 hours autonomous economic agency" possible, freeing users from high-frequency, repetitive decision-making.

In short, the real innovation of AP 2 is not to transform clearing networks such as Visa or stablecoins, but to add a trust semantic layer on top of them about "who is spending money, why they are spending money, and whether it can be traced if it exceeds the authorized scope."

It is committed to uniformly solving the problem of confirming AI payment intentions in different clearing systems such as fiat currency and cryptocurrencies, so as to dispel the fundamental concerns of all participants that the agent's behavior is uncontrollable and unverifiable.

x 402 extension: natively embed encrypted payment into the agent's service call process

The core technology of AP2 is designed to make AI agents compatible with existing human-centric financial authorization systems, while the "A2A x 402" extension is designed for future native, on-chain A2A payments. The x 402 extension is jointly promoted by Google, Coinbase, and the Ethereum Foundation.

The technical choice of x402 stems from a long-dormant internet standard: the HTTP 402 status code, which defines "Payment Required." In the past, due to the lack of standardized machine payment methods, this status code was rarely used in practice.

However, when the main callers of the API change from human developers to high-frequency, automated AI agents, the value of this protocol becomes apparent.

Traditional subscription or prepaid payment models are too cumbersome and inefficient for Agents that need to call massive services on-demand, dynamically, and across platforms. The core idea behind x402 is to address this problem by natively coupling API calls with payment.

Its workflow is designed to be extremely simple and automated:

1. The AI Agent calls a paid service API.
2. The service's server directly returns a 402 Payment Required response containing the information required to complete the payment (such as the recipient address, amount, and token type).
3. The Agent's built-in wallet or payment module parses this "payment bill" and automatically completes the payment on the chain (such as using USDC).
4. The agent carries the on-chain payment credentials and re-initiates the API request.
5. After the server verifies the payment, it immediately returns the data or service results required by the Agent.

This process may seem simple, but it can leverage the real-time settlement and highly programmable features of stablecoins to have a significant impact on the business model of AI Agent services.

Impact on AI Agents:

• Achieving true "pay-as-you-go" : Agents no longer need to go through the traditional manual process of "registering an account -> binding a credit card -> selecting a subscription plan -> waiting for service activation." They can dynamically discover any service that complies with the x402 standard on the network and complete payment and usage within milliseconds, laying the foundation for the agent's autonomy and exploration capabilities.
• Extreme cost efficiency : Agents can pay far more frequently than humans, and their parallelized task processing capabilities enable extremely granular micropayments and streaming payments. x402 enables agents to precisely pay based on the number of API calls, the amount of data returned (tokens), and the duration of computation. This seamlessly aligns resource consumption with cost, avoiding the resource waste associated with traditional subscription models.

Impact on AI service providers:

• The payment system is lowered to the protocol layer : x402 builds "access as quote, payment as service" capabilities directly into the communication protocol layer. Developers no longer need to build complex billing, account, and subscription management systems. They can focus on developing core services and market them with granular pricing for any API, data shard, or even a page component.
• Optimizing Cash Flow and Global Settlement : Leveraging stablecoins, service providers can achieve instant, low-cost global settlement, completely eliminating the lengthy settlement cycles and high fees associated with traditional cross-border payments. This provides unprecedented convenience for reconciling ultra-high-frequency, extremely small transactions, significantly lowering the barrier to commercialization for individual developers and small teams of AI-powered services.

Summary and Outlook: Dual Tracks in Parallel, Ecosystem Emerges

The value of the AP 2 protocol lies not in its seemingly simple technical details, but in the fact that it provides the last piece of the business closed loop for the technological evolution path of MCP (connection) + A 2 A (collaboration) - value settlement .

By empowering agents with reliable transaction capabilities, it lays the first standardized track for the entire industry to transition from the "AI tool" era to the true "agent economy" era.

Google's layout clearly shows its intention: on the one hand, by being compatible with traditional businesses, it accelerates the implementation of Agent in mainstream scenarios such as e-commerce and subscriptions, formulates industry standards, and enables e-commerce platforms to quickly "adapt" to the intervention of AI ; on the other hand, by embracing crypto-native solutions, it also establishes standards for on-chain Agent-to-Agent payments.

Opportunities and Challenges: The Crossroads of Crypto-Native Agents

The completion of AP2 payment capabilities will undoubtedly unlock a large number of application scenarios, such as 24/7 independent financial management, enterprise automated procurement and renewal, etc., which will promote the penetration of the Agent-to-Agent economic model.

However, AP 2 is a top-down authorization framework driven by tech giants with the primary goal of solving their core business ecosystem problems. Crypto payments play a role of being "compatible" and "supported."

This creates a positive stimulus for crypto-native agent protocols. Currently, agent products that truly embrace the core values of Web 3, such as decentralization, censorship resistance, and privacy protection, have yet to achieve key technological breakthroughs and lack a clear PMF.

As industry standards become increasingly clear, who can create products with native cryptographic qualities and innovative designs will be a watershed in the future competition for crypto AI protocols.

Despite the uncertainties ahead, some crypto protocols have already begun actively developing around AP 2 and the possibilities it brings. From the initial partnerships, we can see a nascent ecosystem taking shape:

Standards and Infrastructure: Coinbase, as the original proponent of the x402 payment standard, is actively promoting its implementation; the Ethereum Foundation is working hard to develop underlying protocols such as ERC-8004 (trust proxy standard).

Entry and Wallet: MetaMask is committed to building a self-hosted AI agent wallet and simplifying the user onboarding process, striving to become a secure entry point for the Agent economy.

Public chain and interoperability: Mesh focuses on optimizing payment routing to ensure the success rate and efficiency of agent payments.

Payment and Application: Companies such as Crossmint and BVNK provide Agents with multi-channel crypto and fiat currency payment capabilities; while platforms such as Questflow have built-in x402 micropayment systems, allowing Agents to be paid according to task results.

Ultimately, the release of AP 2 marks the beginning of the standardization process for the Agent Economy. It brings unprecedented imagination to the industry, but also further concentrates the power to control these new economic rules.

For the crypto industry, this presents both an excellent opportunity to integrate into the mainstream and accelerate adoption, and a critical test for the future dominance of the agent economy. How to leverage this infrastructure while forging a differentiated path embodying the core values of Web 3 will be a track worth watching in the coming year.

About Movemaker

Movemaker, authorized by the Aptos Foundation and co-founded by Ankaa and BlockBooster, is the first official community organization dedicated to promoting the development of the Aptos ecosystem in the Chinese-speaking region. As the official representative of Aptos in the Chinese-speaking region, Movemaker is committed to building a diverse, open, and prosperous Aptos ecosystem by connecting developers, users, capital, and numerous ecosystem partners.

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