The burgeoning world of decentralized AI has found a new ally in the Model Context Protocol (MCP)—a revolutionary framework that’s reshaping how agents interact with data and computational resources. Born out of an experimental project at Anthropic, MCP has swiftly become the linchpin of agentic communication, akin to how HTTP transformed web interactions. As of 2025, its adoption across major AI platforms signals a paradigm shift, with intriguing implications for the Web3 landscape.
The Rise of MCP in AI
MCP’s journey began modestly, aimed at streamlining prototype agents’ interactions with document stores. However, its potential was quickly realized, and by mid-2024, open-source implementations had taken the research community by storm. A flurry of community-driven extensions soon emerged, adding layers of functionality like secure credential exchange and federated learning. Fast forward to early 2025, and MCP has become the backbone of platforms like OpenAI, Google DeepMind, and Meta AI, cementing its status as the go-to protocol for agentic communications.
“MCP is not just a protocol; it’s a new language for AI systems,” explains Dr. Emily Tran, a researcher at MIT. “Its ability to integrate smart agents with diverse data sources is, frankly, game-changing.”
At its core, MCP employs a lightweight client-server model, facilitating parallel context sourcing from multiple servers. This architecture revolves around three primitives—Tools, Resources, and Prompts—enabling agents to collaborate seamlessly. Tools execute specialized tasks, Resources fetch contextual data, and Prompts guide reasoning processes. With these building blocks, MCP ensures consistent, interoperable interactions across varied infrastructures.
Web3 and MCP: A Perfect Match?
Now, here’s where it gets interesting. The intersection of MCP with Web3 technologies is poised to unlock a new era for decentralized AI. Imagine blockchain datasets and protocols operating as MCP servers or clients—a vision that could bring seamless access to on-chain data and smart contract functionalities. Analysts foresee blockchain nodes exposing transaction histories through MCP servers, while DeFi platforms offer composable operations via MCP interfaces. This mirrors the innovative strides seen in Clearmatics’ New DeFi Derivatives, which are expanding the horizons of decentralized finance.
“Incorporating MCP into Web3 could catalyze a trust-minimized fabric for intelligent agents,” suggests Alex Kim, a blockchain strategist. “It’s about making blockchain data readily available for AI applications.”
Traditional crypto gateways like exchanges, wallets, and explorers are already adapting to this new paradigm, acting as MCP clients that query and process context uniformly. Picture an AI agent simultaneously interfacing with Aave’s lending markets, Layer0’s cross-chain bridges, and MEV analytics—using a single, coherent programming interface.
The Evolution of MCP Networks
While MCP is powerful, its evolution toward complete networks is inevitable. Today, using MCP requires a deep understanding of client-server endpoints. But the future? It promises dynamic discovery, search capabilities, and ratings of MCP servers and clients. Authentication and identity mechanisms are crucial missing pieces, essential for widespread MCP adoption. This evolution is reminiscent of the transformative potential seen in TradeOS’s integration into Cointelegraph Accelerator, which aims to redefine global trade infrastructure.
Project Namda, led by MIT’s CSAIL and the MIT-IBM Watson AI Lab, is a prime example of progress in this area. Launched in 2024, Namda is pioneering scalable, distributed frameworks built on MCP’s foundations. It creates an open ecosystem where agents can seamlessly exchange context and coordinate complex workflows. Namda’s decentralized registry, inspired by blockchain techniques, ensures verifiable agent identities and trusted multi-party workflows.
“Project Namda is pushing the boundaries of what’s possible with MCP,” says Dr. Ravi Patel, one of Namda’s lead researchers. “We’re seeing efficient federated learning across global testbeds without compromising on interoperability or security.”
A New Foundation for Decentralized AI
For years, decentralized AI struggled to find its footing in mainstream applications. But with MCP’s rise, a new foundation is emerging. The combination of Web3’s trustless, verifiable computations with MCP’s agentic framework could be the breakthrough needed to power a new generation of AI infrastructure.
And yet, questions linger. Can MCP truly scale to meet the demands of rapidly evolving AI landscapes? Will Web3’s decentralized ethos mesh seamlessly with MCP’s structured frameworks? As 2025 unfolds, these questions will undoubtedly shape the future of decentralized intelligent systems—marking a pivotal moment in the ongoing saga of AI innovation.
Source
This article is based on: The Protocol of Agents: Web3’s MCP Potential
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Steve Gregory is a lawyer in the United States who specializes in licensing for cryptocurrency companies and products. Steve began his career as an attorney in 2015 but made the switch to working in cryptocurrency full time shortly after joining the original team at Gemini Trust Company, an early cryptocurrency exchange based in New York City. Steve then joined CEX.io and was able to launch their regulated US-based cryptocurrency. Steve then went on to become the CEO at currency.com when he ran for four years and was able to lead currency.com to being fully acquired in 2025.
