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đź’ˇWhat is MCP? Model Context Protocol (MCP) is an open standard that allows AI systems to directly interact with external tools (and blockchain data) through structured workflows. Key takeaways: * Institutions still depend on manual workflows and siloed teams to navigate blockchain analysis * MCP brings conversational language into blockchain data analytics
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The CLARITY Act is closer than ever to passing into law. Just last week, the bill made it out of the Senate Banking Committee, a year after it was first introduced last May. Even with bipartisan discord, (and plenty of reservations still regarding the bill’s regulation of stablecoin yield
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Key takeaways: * Compliance systems flag risk, but they rarely explain it * Passing a compliance check doesn’t mean understanding counterparty behavior * Intelligence systems turn activity into explainable patterns and decisions * Both layers depend entirely on the quality of the underlying data 💡What’s the difference between crypto compliance and crypto
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Key takeaways: * Blockchain data needs a system with multiple layers to be compliant * Most companies are missing that data foundation unifying interpretation * Data without standardized interpretation can cause huge differences in a compliance stack * AI systems need normalized, standardized data to function without human interference * Crypto compliance data stacks now
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Key takeaways: * More crypto analytics and investigations are being assisted by AI * AI systems can use MCP to turn prompts into defined operations * AI can still hallucinate with MCP, risks are still involved * The quality of the data layer will determine the quality of the crypto investigation or analysis đź’ˇWhat
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Key takeaways: * Crypto wallets used to only need to send, receive, and show balances * The crypto industry’s growth means that users require more from their wallets — like portfolio views, trading capabilities, staking, strategic AI assistance * Traditional wallet infrastructure wasn’t built to support this level of execution * Allium’s
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Key takeaways: * Blockchain data is not as straightforward as its transparent nature makes it seem * Different blockchains define data differently * Small differences in data interpretation can snowball into large inconsistencies * Blockchain isn’t yet a system of record — but it can be with the right crypto data infrastructure 💡What is
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Blockchain data infrastructure is increasingly used by institutions, not just crypto native teams. Banks, fintech companies, trading firms and compliance platforms now rely on onchain data to power production systems, risk monitoring, analytics and payment infrastructure. As this shift occurs, the expectations placed on blockchain data providers are changing. Institutional
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Originally published in Liberty Street Economics (Federal Reserve Bank of New York) on November 25, 2025, by Rod Garratt and Michael Junho Lee. The authors argue that payment stablecoins' key advantage comes not from their monetary form but from their transfer over permissionless blockchains, which enable borderless, peer-to-
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AI agents are beginning to transact autonomously — paying for compute, APIs, and services in real time. Some use stablecoins or blockchain rails; others connect to existing payment networks or bank APIs. Whatever the settlement method, a new class of agentic payments is emerging — and it exposes a critical gap: the
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Why blockchain data is so hard to use, and why enterprises now need an operating system for onchain data
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This article was originally published in Financial Columnist. You can find the original post on their website here." This article is adapted from a presentation delivered at the Federal Reserve Bank of New York in April, 2025, where Ethan Chan (CEO, Allium) shared insights on the state of on-