Etherscan has released the "Build with AI" toolkit, allowing developers and AI agents to access certified real-time on-chain data across more than 60 EVM-compatible chains via MCP, CLI, and Skills.

The toolkit connects to the same Etherscan API data layer as the etherscan.io website, supporting queries for on-chain native coin and token balances, regular transactions, internal transactions, transaction receipts, contract information, Gas prices, and event logs. The available endpoints and access permissions for different chains still depend on the user's API plan.

Etherscan MCP is aimed at agents that can call tools like Claude, ChatGPT, and Codex, enabling developers to request on-chain information in natural language through the official MCP endpoint. This service offers 20 tools that can cover all networks supported by Etherscan in a single connection, authenticated via API key.

Etherscan CLI can be used in terminals, scripts, and CI processes, generating JSON by default while also supporting table and CSV formats; its purpose is to allow developers to embed queries for addresses, transactions, contracts, and on-chain events into automated development and operational processes without requiring agents to scrape web pages or parse unstructured pages.

The Skills module provides installable professional task packages, including Orchestrator, Contract Review, Transaction Debugger, and Etherscan Flow. Flow can trace the flow of funds between addresses and write case files, the contract review module explains the behavior of verified contracts, the transaction debugger restores the execution content and failure reasons of transactions, while Orchestrator routes tasks to suitable tool interfaces.

Etherscan emphasizes that Skills require addresses, amounts, and transaction hashes to be obtained through real-time API calls, rather than being completed by the model; the toolkit is read-only and adheres to existing API usage quotas and rate limits. Developers can use the official llms.txt, llms-full.txt, or Docs MCP to provide contextual documentation to agents, reducing the risk of misuse of interface parameters, chain IDs, and data formats.

In terms of market mechanisms, on-chain data service providers are shifting their business, originally aimed at human web browsing and developer REST calls, to a structured data infrastructure for agents. Developers and security teams can delegate contract reviews, transaction troubleshooting, fund flow tracking, address monitoring, and preliminary risk control screening to AI workflows, with demand shifting towards Etherscan API plans, proxy development tools, wallet security services, compliance analysis, and security audit platforms; meanwhile, API limits, data latency, index integrity, and model misinterpretation of on-chain semantics will still restrict automated decision-making. Beneficiaries will be platforms that possess high-quality indexed data, developer distribution channels, and workflow integration capabilities, while services relying on manual web searches and screenshot-based on-chain analysis will face efficiency pressures.

Source: Public Information