Author: @BlazingKevin_, the Researcher at Movemaker

Google's recently released AP2 protocol outlines the underlying rules for payments and transactions in the upcoming Agent economy. Its core task is to complete the final piece of the puzzle from "AI Analysis" (based on MPC) and "Agent Execution" (based on A2A) — "Value Settlement," attempting to standardize the payment process of AI Agents, formalize the interaction rules of Agents, and ultimately promote AI Agents that can autonomously conduct business activities on behalf of users.

The primary application scenario of AP2 targets the core areas of traditional internet, such as e-commerce and subscription services. This means its original design intention is to address how to securely delegate payment authorization from humans to AI within the existing business framework. This will directly impact the direction of e-commerce operations, freeing users from the actions of clicking "buy" and "subscribe," and shifting towards "intent delegation" and "rule setting" for AI Agents.

Based on this logic, we need to assess the impact of AP2 on the cryptocurrency industry more cautiously. It is not born for Web3 native scenarios but incorporates cryptocurrency payments (especially stablecoins) as an optional, integrated payment option within its grand framework. Therefore, rather than saying AP2 will trigger an explosion of AI, it provides an interface for cryptocurrency assets to enter mainstream AI applications.

Understanding the Preceding Protocols: MCP and A2A

The existence of AP2 is built upon the development paths of the two preceding protocols, MCP and A2A. Understanding the essence and limitations of these two protocols is key to grasping AP2's true intentions. MCP addresses the connection issue between AI and tools, while A2A attempts to solve the collaboration problem between AI and AI.

What is MCP? Allowing AI to Truly Engage with 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 cannot access real-time information or directly operate any external software. When a user issues a command like "Help me book a flight to Osaka tomorrow," it cannot fulfill this request because it lacks the ability to interact with booking websites.

The introduction of the MCP (Model Context Protocol) is aimed at solving the problem of how AI communicates with the external environment. MCP defines a standardized communication format that allows AI to send requests to external tools (such as databases, APIs) and receive results in return. It can be understood as installing a phone for this "locked room brain."

MCP (Model Context Protocol) is a "standard intercom system" born to break down this locked room.

It is driven by industry giants like Anthropic and aims to solve the problem of how AI can interact with external data and tools (such as databases, software, blockchain) in a standardized manner. Through this "intercom," AI models can issue requests to the outside world in a standard language, while the MCP system is responsible for accurately relaying these requests to the corresponding external tools (such as weather APIs, booking site APIs) and returning the results to AI in a standardized format once the tools have completed their tasks.

However, analyzing the current implementation of MCP, we find that it resembles an "internal phone" that can only dial a few preset numbers.

Currently, the ability of AI to call external tools heavily relies on the vertical integration of platform providers. For example, when Gemini needs to search, it defaults to and exclusively uses Google Search; its code execution also runs in a sandbox environment built by the platform. This model has direct implications for users and developers:

For users: The upper limit of AI's capabilities is locked by the platform. Users cannot choose what they consider to be higher-quality third-party tools (for example, using Perplexity for AI searches or calling specific financial data APIs). As a result, the practicality of AI is greatly limited, and the user experience is bound within the platform's ecosystem.

For developers: This creates a de facto market barrier. Even if developers create AI applications that far exceed the platform's built-in tools in a certain field, they cannot be fairly discovered and called by mainstream AI Agents. Innovation is suppressed, and market competition is confined within a closed, platform-dominated collaborative system.

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

If MCP allows AI to have the "hands and feet" to operate tools, then the A2A (Agent-to-Agent) protocol enables independent AI Agents to learn how to "communicate and collaborate." It is built on top of MCP and defines a set of universal rules that allow independent AI Agents developed by different companies and developers to discover each other, understand each other's capabilities, and collaboratively complete complex tasks that a single Agent cannot handle.

The significance of A2A lies in upgrading the task processing model of MCP from "individual combat" to "project subcontracting." For example, when a user presents a complex requirement like "plan a beach party in Hawaii next month," under the closed system of only MCP, individual Agents can only clumsily call the limited tools allowed by the platform one by one.

However, in the A2A concept, individual Agents can act as "contractors." They can break down the task and publish requests in the A2A network, seeking specialized "travel Agents," "catering Agents," and "event planning Agents" to collaborate on completion. This shift in model will have far-reaching impacts:

For users: The capabilities of AI Agents will achieve exponential leaps. Users can confidently delegate extremely complex, cross-domain tasks because AI is no longer a simple operator of tools but a coordinator of resources.

For the industry: A2A aims to create an open, interoperable Agent service market. It seeks to solve three core issues: how to discover (establishing a mechanism similar to an Agent app store), how to understand (defining a standardized descriptive language for Agent capabilities), and how to collaborate (standardizing task allocation and progress synchronization processes). Once this system matures, any Agent developer that meets the standards can register their services and be fairly chosen by the market.

Core Mechanism of AP2: Establishing a Trust and Authorization Framework for Agent Transactions

The MCP and A2A protocols address the questions of "what Agents can do" and "how to collaborate," but this immediately raises a more challenging business dilemma: when Agents begin to autonomously execute operations involving funds, who is responsible for the legality and consequences of these actions?

Traditional online payment systems base their risk control logic on a fundamental premise: there is a human user actively and in real-time performing operations in front of the screen. Any automated payment request initiated by a non-human will be flagged as high-risk behavior by the existing financial system. This is the most fundamental barrier to the formation of the Agent economy. Specifically, a transaction request initiated by AI presents three unanswered questions for merchants and payment networks:

Authorization proof: How to confirm that the user has genuinely authorized the AI to conduct this transaction?

Intent fidelity: Does the AI's specific request (such as purchase quantity, price) accurately reflect the user's true intent, especially when the user is not monitoring in real-time?

Liability attribution: If a transaction goes wrong, who should bear the resulting losses?

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

The core technology of AP2 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 make a payment on a website, an authorization window pops up on your phone. What AP2 does is this.

After the Agent completes preliminary work such as product research and price comparison, it will generate a "shopping cart" containing all transaction details and present it to the user. The execution of the transaction must wait for the user to conduct a final review and sign confirmation.

Impact analysis: Real-time authorization is the initial form of Agent payment; it lowers the user's entry threshold but does not fully leverage the autonomy of the Agent. Its main value lies in optimizing the decision-making process before the transaction, but the final "last step" still requires human intervention.

2. Delegated Authorization (Intent Mandate)

This is the transformative part of AP2. Users can pre-set a complex set of conditional delegation instructions. For example: "Only execute the purchase process automatically when the price of the Tesla Model Y drops by more than 20,000 yuan, using funds from Account A; if Account A is insufficient, then use Account B."

To make this "forward delegation" trustworthy and secure, the implementation logic of AP2 is based on Verifiable Credentials (VCs):

The user's complex delegation conditions will be compiled into a tamper-proof, digitally signed "transaction contract" (i.e., VC).

At every key step of task execution, the AI Agent must present this "contract" to prove the legality of its actions.

All execution steps will also generate corresponding VC records, ensuring the entire process is auditable.

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

For users: This makes a truly "24/7 autonomous economic agent" possible, liberating users from high-frequency, repetitive decision-making.

In summary, the true innovation of AP2 is not to transform clearing networks like Visa or stablecoins but to add a trust semantic layer about "who is spending money, on what basis, and can be traced beyond the authorization limits" on top of them.

It aims to unify the solution to the confirmation of AI payment intent across different clearing systems, such as fiat and cryptocurrency, thereby dispelling all parties' fundamental concerns about the uncontrollable and unverifiable behavior of Agents.

x402 Extension: Natively Embedding Cryptocurrency Payments into the Service Calling Process of Agents

The core technology of AP2 is designed to make AI Agents compatible with existing, human-centered financial authorization systems, while the "A2A x402" extension is designed for future native, on-chain A2A payments. The x402 extension is jointly promoted by Google, Coinbase, and the Ethereum Foundation.

The technical selection of x402 originates from a long-idled internet standard — the HTTP 402 status code, defined as "Payment Required." In the past, due to the lack of standardized machine payment methods, this status code was almost never practically applied.

However, when the primary callers of APIs shift from human developers to high-frequency, automated AI Agents, the value of this protocol becomes evident.

Traditional subscription or prepaid models are too cumbersome and inefficient for scenarios where Agents dynamically and cross-platform call vast services on demand. The core idea of x402 is to solve this problem by natively coupling API calls with payments.

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 needed to complete the payment (such as the payment 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-chain (e.g., using USDC).
4. The Agent carries the on-chain payment proof and re-initiates the API request.
5. After verifying the payment, the server immediately returns the data or service results required by the Agent.

This process seems simple but can leverage the real-time settlement and highly programmable features of stablecoins, significantly impacting 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 follows the x402 standard in the network and complete payment and usage in milliseconds, providing a foundation for the autonomy and exploratory capabilities of Agents.

Extreme cost efficiency: The payment frequency of Agents far exceeds that of humans, and their parallel task processing capabilities enable them to conduct extremely granular micropayments and flow payments. x402 allows Agents to pay precisely based on API call frequency, returned data volume (tokens), and computation duration, perfectly linking resource consumption with costs and avoiding resource waste under traditional subscription models.

Impact on AI Service Providers:

Diving down the protocol layer of payment systems: x402 directly builds the capability of "access equals quote, payment equals service" at the communication protocol layer. Developers no longer need to build complex billing, account, and subscription management systems; they can focus on developing core services, pricing any API, data shard, or even a page component in a granular manner and bringing it to market.

Optimizing cash flow and global settlement: With stablecoins, service providers can achieve instant, low-cost global settlement, completely freeing themselves from the lengthy settlement cycles and high fees of traditional cross-border payments. This provides unprecedented convenience for reconciling ultra-high-frequency, very small transactions, significantly lowering the barriers for individual developers and small teams to commercialize AI services.

Summary and Outlook: Dual-Track Parallel, Initial Ecosystem Emergence

The value of the AP2 protocol lies not in its seemingly simplistic technical details but in providing the final piece of the puzzle for the commercial closed loop of the technical evolution route of MCP (Connection) + A2A (Collaboration) — value settlement.

By granting Agents reliable transaction capabilities, it lays the first standardized track for the entire industry to transition from the "AI tools" era to the true "Agent economy" era.

Google's layout clearly indicates its intentions: on one hand, by accommodating traditional business, it accelerates the landing of Agents in mainstream scenarios such as e-commerce and subscriptions, establishing industry standards to help e-commerce platforms quickly "adapt" to AI's involvement; on the other hand, by embracing crypto-native solutions, it also sets the standards for on-chain Agent-to-Agent payments.

Opportunities and Challenges: The Crossroads of Crypto-Native Agents

The completion of AP2's payment capabilities will undoubtedly unlock a multitude of application scenarios, such as 24/7 autonomous financial management, automated corporate procurement and renewals, all of which will drive the penetration of the Agent-to-Agent economic model.

However, AP2 is an authorization framework driven top-down by tech giants, with the primary goal of solving their core business ecosystem issues. In this context, crypto payments play a role that is "compatible" and "supported."

This creates a positive stimulus for crypto-native Agent protocols. Currently, truly decentralized, censorship-resistant, privacy-protecting Agent products centered around the core values of Web3 have yet to achieve key technological breakthroughs and lack clear product-market fit (PMF).

Who can create products with a native crypto essence and innovative design as industry standards gradually become clearer will be the watershed for competition in crypto AI protocols moving forward.

Although the path ahead is unclear, some protocols in the crypto industry have already begun actively positioning themselves around AP2 and its possibilities. From the first batch of partners, we can see a preliminary ecosystem beginning to form:

Standards and Infrastructure: Coinbase, as the initial proposer of the x402 payment standard, is actively promoting its implementation; the Ethereum Foundation is working to establish foundational protocols such as ERC-8004 (Trust Agent Standard).

Entry and Wallet: MetaMask is dedicated to creating a self-custodial AI agent wallet and simplifying the user onboarding process, aiming to become a secure entry point for the Agent economy.

Public Chains and Interoperability: Mesh focuses on optimizing payment routing to ensure the success rate and efficiency of Agent payments.

Payments and Applications: Companies like Crossmint and BVNK provide multi-channel crypto and fiat payment capabilities for Agents; platforms like Questflow have already integrated the x402 micropayment system, allowing Agents to receive compensation based on task results.

Ultimately, the release of AP2 marks the initiation of the standardization process for the Agent economy. It brings unprecedented imaginative space to the industry but also further concentrates the power to control these new economic rules.

For the crypto industry, this is both an excellent opportunity to integrate into the mainstream and accelerate adoption, as well as a severe test of dominance over the future forms of the Agent economy. How to leverage this infrastructure while carving out a differentiated path that embodies the core values of Web3 will be a track worth watching in the coming year.

免责声明：本文章仅代表作者个人观点，不代表本平台的立场和观点。本文章仅供信息分享，不构成对任何人的任何投资建议。用户与作者之间的任何争议，与本平台无关。如网页中刊载的文章或图片涉及侵权，请提供相关的权利证明和身份证明发送邮件到support@aicoin.com，本平台相关工作人员将会进行核查。