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Securitize Unveils MCP Server to Power AI Access to Onchain Assets
The server is built on the Model Context Protocol (MCP) — an emerging open standard that connects large language models to external data sources and APIs.
Oct 22, 2025, 1:00 p.m.
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What to know:
- Securitize, a leading platform for tokenized real-world assets (RWAs), has unveiled the Securitize MCP Server, a new integration layer designed to make its asset data easily accessible to both enterprise systems and artificial intelligence tools.
- The server is built on the Model Context Protocol (MCP) — an emerging open standard that connects large language models like Claude or ChatGPT to external data sources and APIs.
Securitize, a leading platform for tokenized real-world assets (RWAs), has unveiled the Securitize MCP Server, a new integration layer designed to make its asset data easily accessible to both enterprise systems and artificial intelligence tools.
STORY CONTINUES BELOW
The server is built on the Model Context Protocol (MCP) — an emerging open standard that connects large language models like Claude or ChatGPT to external data sources and APIs.
The new MCP Server acts as a secure gateway between Securitize’s RWA datasets and modern applications. Instead of developers manually integrating with raw blockchain endpoints or custom APIs, the MCP Server translates data requests into simple, standardized calls, the team shared. That means financial platforms, institutional investors, or even AI assistants can pull real-time information, such as asset supply, distribution, and token metadata, with just a few function calls.
For crypto investors, it means faster, easier access to reliable on-chain information, without needing to code or navigate complex blockchain explorers.
The MCP Server allows users to instantly retrieve lists of tokenized assets, search for specific securities, and access blockchain-level data in a structured format. For example, an AI agent could query details on BUIDL, BlackRock’s tokenized U.S. Treasury fund, or ACRED, Apollo’s tokenized credit fund, and feed those insights directly into portfolio analytics or compliance systems.
For institutions, the integration offers a path toward streamlined interoperability. With data accessible via MCP, banks, custodians, and fintechs can embed tokenized asset insights into their internal tools or client-facing platforms without heavy technical lift. Meanwhile, AI models gain the ability to interact directly with real-world financial instruments.
“In an era where real-world assets (RWAs) are increasingly being represented on blockchain, access to reliable, standardized, and real-time tokenized asset data has become essential for enterprises and developers alike,” the team wrote in a blog post.
Read more: Securitize Expands to Sei, Debuting With Apollo’s $112M Tokenized Credit Fund
AI Disclaimer: Parts of this article were generated with the assistance from AI tools and reviewed by our editorial team to ensure accuracy and adherence to our standards. For more information, see CoinDesk's full AI Policy.
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