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The Rise of MCP: Transforming AI and Blockchain Integration

· 9 min read
Dora Noda
Dora Noda
Software Engineer

What started as an experimental side project at Anthropic has become the de facto standard for how AI systems talk to the outside world. And now, it's going on-chain.

The Model Context Protocol (MCP)—often called the "USB-C port for AI"—has evolved from a clever integration layer into the infrastructure backbone for autonomous AI agents that can read blockchain state, execute transactions, and operate 24/7 without human intervention. Within 14 months of its November 2024 open-source release, MCP has been adopted by OpenAI, Google DeepMind, Microsoft, and Meta AI. Now, Web3 builders are racing to extend it into crypto's most ambitious frontier: AI agents with wallets.

From Side Project to Industry Standard: The MCP Origin Story​

Anthropic released MCP in November 2024 as an open standard that lets AI models—particularly large language models like Claude—connect to external data sources and tools through a unified interface. Before MCP, every AI integration required custom code. Want your AI to query a database? Build a connector. Access a blockchain RPC? Write another one. The result was a fragmented ecosystem where AI capabilities were siloed behind proprietary plugins.

MCP changed this by creating a standardized, bidirectional interface. Any AI model supporting MCP can access any MCP-compatible tool, from RESTful APIs to blockchain nodes, without custom connector code. Harrison Chase, CEO of LangChain, compared its impact to Zapier's role in democratizing workflow automation—except for AI.

By early 2025, adoption had reached critical mass. OpenAI integrated MCP across its products, including ChatGPT's desktop app. Google DeepMind built it natively into Gemini. Microsoft incorporated it across its AI offerings. The protocol had achieved something rare in tech: genuine interoperability before market fragmentation could set in.

The November 2025 specification update—marking MCP's first anniversary—introduced governance structures where community leaders and Anthropic maintainers collaborate on protocol evolution. Today, over 20 live blockchain tools use MCP to pull real-time price data, execute trades, and automate on-chain tasks.

Web3's MCP Moment: Why Blockchain Builders Care​

The marriage of MCP and blockchain addresses a fundamental friction in crypto: the complexity barrier. Interacting with DeFi protocols, managing multi-chain positions, and monitoring on-chain data requires technical expertise that limits adoption. MCP offers a potential solution—AI agents that can handle this complexity natively.

Consider the implications. With MCP, an AI agent doesn't need separate plugins for Ethereum, Solana, IPFS, and other networks. It interfaces with any number of blockchain systems through a common language. One community-driven EVM MCP server already supports over 30 Ethereum Virtual Machine networks—Ethereum mainnet plus compatibles like BSC, Polygon, and Arbitrum—enabling AI agents to check token balances, read NFT metadata, call smart contract methods, send transactions, and resolve ENS domain names.

The practical applications are compelling. You could tell an AI: "If ETH/BTC swings by more than 0.5%, automatically rebalance my portfolio." The agent pulls price feeds, calls smart contracts, and places trades on your behalf. This transforms AI from passive advisor to active, 24/7 on-chain partner—seizing arbitrage opportunities, optimizing DeFi yields, or guarding portfolios against sudden market moves.

This isn't theoretical. CoinGecko now lists over 550 AI agent crypto projects with a combined market cap exceeding $4.34 billion. The infrastructure layer connecting these agents to blockchains runs increasingly on MCP.

The Emerging MCP Crypto Ecosystem​

Several projects are leading the charge to decentralize and extend MCP for Web3:

DeMCP: The First Decentralized MCP Network​

DeMCP positions itself as the first fully decentralized MCP network, offering SSE proxies for MCP services with Trusted Execution Environment (TEE) security and blockchain-based trust. The platform provides pay-as-you-go access to leading LLMs like GPT-4 and Claude via on-demand MCP instances, payable in stablecoins (USDT/USDC) with revenue sharing for developers.

The architecture uses stateless MCP where each API request spawns a new server instance, prioritizing isolation, scalability, and modularity. Separate tools handle exchanges, chains, and DeFi protocols independently.

However, the project illustrates the broader challenges facing MCP crypto ventures. As of early 2025, DeMCP's token had a market cap of approximately $1.62 million—and had dropped 74% within its first month. Most MCP-based projects remain in proof-of-concept stages without mature products, creating what observers call a "crisis of trust" driven by lengthy development cycles and limited practical applications.

DARK: Solana's AI + TEE Experiment​

DARK emerged from the Solana ecosystem, initiated by former Marginfi co-founder Edgar Pavlovsky. The project combines MCP with TEE to create secure, low-latency on-chain AI computations. Its MCP server, powered by SendAI and hosted on Phala Cloud, provides on-chain tools for Claude AI to interact with Solana through a standardized interface.

Within a week of launch, the team deployed "Dark Forest"—an AI simulation game where AI players compete in TEE-secured environments while users participate through predictions and sponsorship. The backing developer community, MtnDAO, is among Solana's most active technical organizations, and Mtn Capital raised $5.75 million in seven days for its Futarchy-model investment organization.

DARK's circulating market cap sits around $25 million, with expectations of growth as MCP standards mature and products scale. The project demonstrates the emerging template: combine MCP for AI-blockchain communication, TEE for security and privacy, and tokens for coordination and incentives.

Phala Network: AI-Agent Ready Blockspace​

Phala Network has evolved since 2020 into what it calls "AI-Agent Ready Blockspace"—a specialized blockchain environment for automated AI tasks. The project's defining feature is TEE technology that keeps AI computations private and encrypted across multiple blockchains.

Phala now offers production-ready MCP servers featuring full Substrate-based blockchain integration, TEE worker management with attestation verification, and hardware-secured execution environments supporting Intel SGX/TDX, AMD SEV, and NVIDIA H100/H200. The platform provides dedicated MCP servers for Solana and NEAR, positioning itself as infrastructure for the multi-chain AI agent future.

The Security Question: AI Agents as Attack Vectors​

MCP's power comes with proportional risks. In April 2025, security researchers identified multiple outstanding vulnerabilities: prompt injection attacks, tool permissions where combining tools can exfiltrate files, and lookalike tools that can silently replace trusted ones.

More concerning is research from Anthropic itself. Investigators tested AI agents' ability to exploit smart contracts using SCONE-bench—a benchmark of 405 contracts actually exploited between 2020 and 2025. On contracts exploited after the models' knowledge cutoffs, Claude Opus 4.5, Claude Sonnet 4.5, and GPT-5 collectively developed exploits worth $4.6 million in simulation.

This cuts both ways. AI agents capable of finding and exploiting vulnerabilities could serve as autonomous security auditors—or as attack tools. The same MCP infrastructure enabling legitimate DeFi automation could power malicious agents probing for smart contract weaknesses.

Critics like Nuno Campos of LangGraph caution that current AI models don't consistently use tools effectively. Adding MCP doesn't guarantee an agent will make correct calls, and the stakes in financial applications are substantially higher than in traditional software contexts.

The Technical Integration Challenge​

Despite enthusiasm, MCP promotion in crypto faces significant hurdles. Different blockchains and dApps use varying smart contract logic and data structures. A unified, standardized MCP server requires substantial development resources to handle this heterogeneity.

Consider the EVM ecosystem alone: 30+ compatible networks with distinct quirks, gas structures, and edge cases. Extend this to Move-based chains like Sui and Aptos, Solana's account model, NEAR's sharded architecture, and Cosmos's IBC protocol, and the integration complexity multiplies rapidly.

The current approach involves chain-specific MCP servers—one for Ethereum-compatible networks, another for Solana, another for NEAR—but this fragments the promise of universal AI-to-blockchain communication. True interoperability would require either deeper protocol-level standardization or an abstraction layer that handles cross-chain differences transparently.

What Comes Next​

The trajectory seems clear even if the timeline remains uncertain. MCP has achieved critical mass as the standard for AI tool integration. Blockchain builders are extending it for on-chain applications. The infrastructure for AI agents with wallets—capable of autonomous trading, yield optimization, and portfolio management—is materializing.

Several developments to watch:

Protocol Evolution: MCP's governance structure now includes community maintainers working with Anthropic on specification updates. Future versions will likely address blockchain-specific requirements more directly.

Token Economics: Current MCP crypto projects struggle with the gap between token launches and product delivery. Projects that can demonstrate practical utility—not just proof-of-concept demos—may differentiate themselves as the market matures.

Security Standards: As AI agents gain real-money execution capabilities, security frameworks will need to evolve. Expect increased focus on TEE integration, formal verification of AI agent actions, and kill-switch mechanisms.

Cross-Chain Infrastructure: The ultimate prize is seamless AI agent operation across multiple blockchains. Whether through chain-specific MCP servers, abstraction layers, or new protocol-level standards, this problem must be solved for the ecosystem to scale.

The question isn't whether AI agents will operate on-chain—they already do. The question is whether the infrastructure can mature fast enough to support the ambition.

BlockEden.xyz provides enterprise-grade blockchain RPC services across multiple networks, offering the reliable infrastructure that AI agents need for consistent on-chain operations. As MCP-powered AI agents become more prevalent, stable node access becomes critical infrastructure. Explore our API marketplace for production-ready blockchain connectivity.

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