Fetch.ai Launches AI Agent Enabling Natural Language Access to 30+ EVM Chains

On May 27, Fetch.ai shared news of the launch of its new AI agent named uagent-evm-mcp on X. This tool enables interaction with over thirty EVM-compatible blockchains using plain English prompts. The core feature relies on natural language AI to simplify access to complex blockchain data. Users can request balances, token details, transaction records, or contract events through simple queries. This integration removes the need to know specific Web3 interfaces or blockchain protocols manually. The move aims to broaden access for users without deep blockchain programming experience.

How Fetch.ai’s AI agent Bridges AI Models and Blockchains

The agent serves as a link between AI models and multiple blockchain networks. It hides technical details by offering a unified interface across many EVM networks. Supported networks include Ethereum, Polygon, Arbitrum, Avalanche, and other popular chains. Developers can query balances, metadata, and transactions without writing low-level blockchain code. Smart contract events and NFT ownership checks become accessible through simple user prompts. The tool transforms English questions like “What is the ETH balance?” into clear queries. Responses arrive in structured formats matching blockchain context requirements for developers and users.

Fetch.ai’s AI agent uses the Model Context Protocol as its communication layer with blockchain data. This protocol ensures compatibility across diverse networks without manual RPC or SDK setups. Developers can retrieve block details, transaction receipts, and contract information easily. It allows agents to monitor smart contract events or estimate gas fees without effort. Integrating this layer reduces the development time required for blockchain-related application builds. Users benefit from simplified query flows while developers avoid complex configuration tasks.

Fetch.ai’s ASI:One A Framework for AI Agents

ASI:One platform provides the underlying framework for running intelligent blockchain agents. This model uses a multi-step reasoning design to make logical decisions autonomously. Fetch.ai’s ASI:One integrates with external APIs and tools for more functions. Agents built on this platform can act on instructions given in plain language. They can fetch data, monitor events, or trigger contract functions based on user requests. This approach turns complex blockchain operations into user-friendly and everyday actions. Developers benefit from quick setup and a consistent interface across multiple blockchain systems.

The new AI Agent shows how conversational systems can interact with blockchain networks. Although built in TypeScript, it serves users who lack programming expertise effectively. Custom agents, analytics tools, and Web3 assistants can leverage this streamlined interface. Supported networks span Ethereum, Optimism, Arbitrum, and other chains in the EVM ecosystem. Users can perform balance checks, retrieve token metadata, or filter contract events easily. This design highlights how Fetch.ai’s AI agent can simplify standard blockchain workflows. It provides clear guidance for operations without backend complexities to end users.

Natural Language AI Simplifies Blockchain Access for Users

This sector of AI integration brings an intuitive interface to decentralized systems. Users can query data with everyday language, avoiding complex code or commands. This method could lower barriers for non-technical participants exploring blockchain solutions. Developers in multi-chain settings may find building cross-network applications more efficient. The approach simplifies the monitoring of events and data across different blockchain environments. Overall, this tool demonstrates how AI can make decentralized systems more approachable. This innovation may support broader adoption by making blockchain tasks feel familiar.

Making Decentralized Systems More Approachable With AI

The uagent-evm-mcp is now available on Agentverse for immediate integration into blockchain projects. It works with any Model Context Protocol-compatible model, including Fetch.ai’s ASI:One modules. Users may fork and adapt the agent to suit various conversational and analytics needs. Minimal setup requirements allow quick deployment across EVM networks for diverse use cases. Developers can create assistants or analytics tools that operate in a blockchain context. This agent may influence future AI-driven blockchain applications by simplifying strong queries. Its flexibility supports use in smart contract analytics, automated monitoring, or multi-chain functions.