News listGemini launches Agentic Trading: Enabling Claude and ChatGPT to place orders directly on regulated exchanges and execute strategy trading
動區 BlockTempo2026-04-28 00:34:38

Gemini launches Agentic Trading: Enabling Claude and ChatGPT to place orders directly on regulated exchanges and execute strategy trading

ORIGINALGemini 推出 Agentic Trading:讓 Claude、ChatGPT 直接下單受監管交易所,執行策略交易
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Gemini has officially launched its Agentic Trading feature, becoming the first regulated crypto exchange in the U.S. to allow AI agents to directly integrate and execute automated trades. The platform is built on the Model Context Protocol (MCP) open standard, enabling AI models such as Anthropic Claude and OpenAI ChatGPT to execute buy and sell orders on behalf of users via API. The initial release features three modules covering real-time market data, spread analysis, and historical K-line data. (Previous coverage: Coinbase launches Agentic Wallets: enabling AI agents to autonomously trade, pay, and earn, integrated with the x402 protocol) (Background: IPO dreams shattered! Gemini faces class-action lawsuit for "misleading investors," stock plunges 80% with 25% layoffs and exits from multiple countries) The official blog announced that Agentic Trading is now live—the first feature from a regulated U.S. crypto exchange that allows AI agents to execute trading operations directly. Unlike traditional API integrations that require manual confirmation for every order, this system grants AI models full access to exchange functions, handling everything from market data queries to order execution autonomously. Gemini chose the Model Context Protocol (MCP) as the underlying standard for this system. MCP is an open protocol spearheaded by Anthropic, designed to allow AI models to connect to external tools and services through a unified interface. By integrating its entire trading API into MCP, Gemini ensures that any MCP-compatible AI model—including Anthropic Claude and OpenAI ChatGPT—can gain full access to the exchange's capabilities. The initial launch includes three modular "Trading Skills": Get Market Data for real-time price information, Find the Spread for bid-ask analysis, and Retrieve Candles for historical K-line data. The strategy coverage ranges from basic buy/sell orders to complex multi-leg positions. In its announcement, Gemini explicitly stated that this is not merely a feature launch, but a redefinition of the trading paradigm: "We believe this is the beginning of a fundamental shift in how people interact with financial markets," adding, "Agentic trading is not just a feature, but a new paradigm—AI handles execution, patterns, and discipline, while you focus on strategy and goals." The timing is intriguing: Gemini announced a 25% workforce reduction in February this year, simultaneously exiting the EU, UK, and Australian markets to concentrate resources on the U.S. domestic market. Returning with a high-profile Agentic Trading launch signals a clear shift: abandoning geographic expansion to capture the product high ground of the next cycle through AI agent infrastructure. The stock market reaction was muted, with GEMI rising only 0.25% to $4.40 that day. While it has gained 7% over the past month, it remains down 55% year-to-date. Competition in this space is quietly taking shape. The x402 protocol, incubated by Coinbase and now under the Linux Foundation, is similarly designed for on-chain payments and interactions for AI agents; meanwhile, the Stripe-backed Tempo network has launched the Machine Payments Protocol, focusing on automated settlement scenarios between AI agents. By choosing MCP—an open standard led by Anthropic—as its backbone rather than building a proprietary protocol, Gemini has ensured that Agentic Trading is natively compatible with all MCP-supported AI models on the market. Theoretically, this allows for much faster ecosystem expansion compared to closed solutions. Whether AI agents can truly become the mainstream interface for retail and institutional trading may reach a turning point by 2026.
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Source:動區 BlockTempo
Published:2026-04-28 00:34:38
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