Type "create a card" in Claude, and you'll get a Visa card a few seconds later. But this card isn't for you; it's for AI. A product demonstration video demonstrating the generation of virtual cards for large models is generating a frenzy of discussion on X. Applying for a virtual card for online transactions isn't anything new for ordinary people, but applying for virtual credit cards for AI is another exciting development in the payment sector after the rise of Agent payments. If you follow this field, you'll find similar excitement every few months. In September 2025, it was the x402 protocol, with Coinbase and Cloudflare collaborating to turn the HTTP 402 status code into a native payment channel for Agent payments. In October 2025, Visa and Mastercard simultaneously released their Agent payment protocols. Now it's virtual cards. The Agent payment sector remains highly fragmented; each provider solves a part of the problem, but no one has yet offered a complete solution. This article attempts to answer several questions: What exactly is an Agent virtual card? How does it differ from x402? What problems can virtual cards solve, and what problems can't they solve? And where are the opportunities in this field? Kite is the first Layer 1 blockchain for AI agent payments. This underlying infrastructure enables autonomous AI agents to operate in environments with verifiable identities, programmable governance, and native stablecoin settlements. Founded by senior AI and data infrastructure experts from Databricks, Uber, and UC Berkeley, Kite has completed a $35 million funding round, with investors including PayPal, General Catalyst, Coinbase Ventures, 8VC, and several top investment funds. What is an Agent's Virtual Credit Card? You certainly don't want to hand over your credit card directly to an Agent, just as many people don't install OpenClaw on their primary computer. The reason is simple: the risk exposure is uncontrollable. Ordinary credit cards have no single-transaction spending limit, no merchant restrictions, and cannot be easily cancelled. Once the agent malfunctions or is attacked, your entire account is exposed to risk. Agent virtual cards are not like issuing an ordinary credit card to AI; they are programmable, restricted payment credentials. Each card can have a spending limit set, and if the agent's spending exceeds the preset amount, the transaction will be automatically rejected. You can also suspend or close any card at any time without affecting your underlying bank account. In short, the core value of virtual cards lies in controllability. Taking AgentCard, the virtual card project that attracted attention yesterday, as an example, it operates through a Model Context Protocol (MCP) server. The process is as follows: You first recharge the virtual card provider, and Agent calls an MCP tool, such as "create_card(amount=$50)", and the provider's API immediately issues a one-time prepaid Visa card with the amount precisely locked at $50. The backend has several layers. The MCP server handles authentication and API calls with fintech companies. The agent cannot see the true source of your funds. The card is issued by the issuing bank on the Visa network, and funds are deducted from your pre-linked bank account or credit card. The agent receives a temporary card number for web checkout or API payment, and the card is automatically deactivated after use. Setup takes approximately 5 minutes and can be completed via CLI or configuration file. The entire process is highly isolated; your real card information is never exposed to the agent. What problem does a virtual card aim to solve? What people call "agent-based commerce" is mostly just adding an extra step to the human shopping process. You use ChatGPT to research a pair of headphones and then place your order—that's the first layer. Or you let ChatGPT find the headphones and click to buy, and you confirm the payment—that's the second layer. Or you set a condition for the agent to automatically buy when the price drops below a certain number—that's the third layer. In all three scenarios, the agent uses your payment credentials, and major card organizations and AI labs are already building the underlying protocols for these scenarios. The truly interesting scenarios begin at the fourth layer. Your agent needs to call the API of another large model, such as switching from Anthropic to a cheaper inference model, purchasing an expensive dataset to complete a research task, or hiring another agent to handle a sub-task. In these scenarios, the agent isn't swiping your card for you; it needs its own payment credentials. Currently, developers buy these things for the agent and then grant it access. This isn't called an agent; it's called a proxy. To completely liberate humans (but not completely relinquish trust), a restricted agent payment method is needed, and the programmable nature of virtual cards perfectly meets this need. Why has this problem only emerged now? Because three conditions are currently ripe. The first condition is demand. The booming lobster installation campaigns in major cities around the world are a case in point. The second condition is the supply side. Stripe Issuing already allows the creation and management of virtual cards via API, with complete technology and protocols. The third condition is the involvement of card organizations. Visa and Mastercard simultaneously released their Agent payment protocols, Cloudflare participated in the development of technical standards, and Fiserv became one of the first major payment processors to support these protocols, completing the platformization process. From grassroots entrepreneurs to card organization giants, everyone saw the same thing at the same time: agents need their own financial infrastructure. The Structural Limitations of Virtual Cards Virtual cards solve today's problems, but they inherit an old problem from bank card networks: slow settlement. Most people outside the payments industry don't realize that when you swipe your card at a store, the merchant doesn't receive the money immediately. It takes a day, a few days, and up to 30 days for cross-border payments to receive funds. Visa itself doesn't move the funds; the bank does, and bank settlements are slow and expensive. This problem is amplified for agents. If your agent is buying a lot of tokens from Anthropic and business suddenly takes off, you might run out of funds before the revenue arrives. Virtual cards also have a second limitation: cross-border costs. Cross-border payments using traditional bank cards involve currency exchange, intermediary bank fees, and compliance reviews. For agents that need to access APIs and services globally, these friction costs accumulate rapidly. The third limitation is insufficient programmability. As your agent's transaction volume increases and the number of sub-agents you need to manage grows, the flexibility of virtual cards becomes inadequate. With virtual cards, the main agent must apply for one for each sub-agent individually, or create a new card each time for a few dollars. Understanding these limitations helps explain why the x402 protocol gained attention a few months ago. The essence of x402 is to bypass bank card networks and complete on-chain payments directly at the HTTP layer using stablecoins. For example, suppose your agent needs to call a paid API to obtain real-time data. With virtual cards, you would first need to create a card, register an account on the service provider's website, bind the card, subscribe to a monthly plan, obtain the API key, and then configure it for the agent.

Using x402, the Agent directly sends an HTTP request, the server returns a 402 status code and price, the Agent automatically signs a USDC transfer, the server confirms receipt and returns the data. No registration or subscription is required; payment is based on usage.
The two are not mutually exclusive. Virtual cards are suitable for Agents to use at merchants that accept Visa, for online shopping, SaaS subscriptions, and paying cloud service bills.
... x402 is suitable for direct payments between agents, including API calls, data purchases, and hiring other agents to complete sub-tasks. Currently, most merchants only accept Visa/Mastercard, so virtual cards are the viable solution today. However, for scenarios involving agent API calls and agent-to-agent collaboration, native payment protocols like x402 are more suitable. Another intermediate solution is to use stablecoins to accelerate backend settlement of bank cards. The front end is still card swiping, but the back end becomes instant on-chain settlement. Some say stablecoins will disintermediate bank card networks, but this is a misconception. Stablecoins cannot provide unsecured credit, chargeback rights, or Visa-level anti-fraud capabilities; they are there to accelerate bank card transactions, not to replace them. The three-layer solution is progressive: virtual cards solve compatibility, stablecoins solve settlement speed, and native wallets solve programmability. Your current level depends on the types of counterparties your agent deals with. Three parallel startup tracks: Agent-oriented payment startups will eventually converge on a place many wouldn't expect: machine organizational science. Think about how companies manage employee spending today. Company cards, reimbursement rules, budget centers, approval processes, audit trails. This system is the infrastructure of corporate governance. Now, companies need to equip AI agents with the same things. This means at least three startup tracks are opening up simultaneously. The first is agent-first card issuance platforms. Currently, multiple platforms have entered the market, but most are still at the most superficial level of virtual card issuance. The real moat lies in risk control models, billing logic, and developer experience. For example, the onboarding process doesn't require filling out forms; registration is done via API; the risk control model is based on agent behavior patterns rather than human credit history; and billing logic is based on token consumption rather than monthly bills. The second point is KYA infrastructure. KYA stands for Know Your Agent, corresponding to KYC in traditional finance. When agents become merchants and buyers, understanding your customers becomes understanding your agents. Who developed it? On what model does it run? What are the historical transaction records and behavior patterns? This is a completely new layer of trust. A startup called Skyfire is already doing this, launching the KYAPay protocol, which allows merchants to verify the identity and authorization status of agents. In December 2025, Skyfire partnered with Visa to complete an end-to-end agent shopping demonstration: the agent independently researched products, compared prices, and completed the purchase, with identity verification handled by the KYA protocol and payment processed by Visa's Trusted Agent Protocol. However, by 2026, Skyfire had stopped updating its official website, with no new product or protocol updates. It's fair to say that the entire industry currently lacks a unified standard, making it a highly competitive market. The third point concerns the clearing and auditing network for inter-agent transactions. When a main agent manages dozens of sub-agents, each with its own wallet and transaction records, who will reconcile the accounts? Who will audit them? This presents an opportunity for the "Big Four" accounting firms in the agent economy. History often rhymes. Around 2000, eBay created a marketplace where ordinary people could buy and sell from each other. Individual sellers couldn't access merchant accounts, but PayPal allowed them to receive payments. By the end of that year, PayPal processed 40% of eBay auction payments. Around 2010, independent developers wanted to receive payments online; PayPal and Cybersource could do it, but the process was lengthy and cumbersome. Stripe solved the problem with seven lines of code. The pattern remains consistent: every shift in platform paradigms creates a new batch of merchants that existing payment systems cannot serve. The winners serve merchants that traditional giants deem unworthy of risk assessment. Who are today's new merchants? In 2025, GitHub added approximately 36 million developers. At the Y Combinator Winter 2025, over 95% of the codebases of a quarter of the companies were generated by AI. On Bolt.new, 67% of its 5 million users are not professional developers. Millions of ordinary people who couldn't write production-ready code two years ago are now releasing software. Returning to the initial tweet, giving AI a Visa card to spend money on its own—this may seem like a product feature, but it's actually the starting point of a paradigm shift. From grassroots entrepreneurs to card organization giants, everyone realizes that agents need their own financial infrastructure. But virtual cards, stablecoins, and wallets are just scaffolding. The real change lies deeper. When natural language becomes the native interface for transactions, payments are no longer an independent industry; they become a fundamental capability embedded in every conversation. Back then, individual sellers on eBay didn't care about the technological differences between ACH and credit card networks. They just needed something to register and receive payments, and PayPal provided that. Today, tens of millions of Vibe Coders and their agents don't care about the underlying debate between bank cards and stablecoins. They just need to say a word, and the money is there. Whoever does it first will be the next PayPal.