Etherscan
Ethereum blockchain explorer
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About Etherscan
Etherscan is the leading blockchain explorer and analytics platform for Ethereum and 60+ EVM-compatible chains. Its core business is indexing and presenting on-chain data—transactions, wallet balances, smart contract code, token transfers, and gas fees—through an easy-to-use web interface and a widely adopted API.
Its competitive moat lies in being the de facto standard for blockchain data access: comprehensive indexing, reliable uptime, and a unified multi-chain experience via Blockscan (BscScan, PolygonScan, etc.). The narrative centers on "transparency infrastructure"—making raw, technical blockchain data readable and verifiable for anyone, from retail users to institutional compliance teams.
The market pain point is that blockchain data is inherently opaque and fragmented. Raw node data is unreadable to most people, and cross-chain activity is scattered across different networks. Etherscan solves this by providing a single, searchable window into the entire history of major chains, plus developer tools (API, webhooks) that power thousands of third-party apps.
In the past six months (March–September 2026), Etherscan launched "Build with AI" (announced Aug 31, 2026), a toolkit including an MCP server, CLI, and AI agent skills. It allows AI assistants like Claude and ChatGPT to query real-time on-chain data across 60+ chains via natural language, directly addressing the AI hallucination problem in crypto—models often fabricate wallet balances or transactions when they lack verified data. The toolkit uses standard API keys and respects rate limits.
Negative aspects: Etherscan is a centralized service—if it goes offline, users must switch to alternatives. Its free API tier is rate-limited (5 calls/second), and paid plans can be costly for high-volume users. Also, while it labels known scam addresses, it cannot prevent fraud; users must still do their own due diligence.
Etherscan expanded to the Sei network by launching Seiscan, deepening its multi-chain explorer capabilities.
It introduced an AI-exclusive API allowing agents to directly query on-chain data across over 60 chains, marking a step toward advanced data accessibility.
Address credit scoring was added to evaluate on-chain credit risk, enhancing analytical tools for users.
Proxy contract historical upgrade records were enabled for improved contract tracking over time.
Support for ZKsync Era indexing will end in January 2026, reflecting strategic network prioritization.
Etherscan's key developments in the past six months center on AI integration and API service adjustments.
On August 31, 2026, Etherscan launched the "Build with AI" toolkit, providing three access methods: an MCP server (mcp.etherscan.io/mcp), a CLI tool (etherscan-cli), and installable AI agent skills. The toolkit covers 60+ EVM chains, offering 20 core functions including balances, transactions, tokens, contracts, logs, gas, and stats. All data comes from real API calls to prevent AI hallucinations, and the free tier supports all networks.
API service changes: Gnosis Chain (ID 100) free tier moved to a shared pool model on July 16, 2026; Moonbeam, Moonriver, and Moonbase Alpha chain support was deprecated on July 31, 2026; Scroll Mainnet and Sepolia were deprecated on April 16, 2026. Starting July 1, 2026, the free tier's maximum records per request was reduced from 10,000 to 1,000, affecting 10 endpoints including transaction and token transfer queries. The "Get Internal Transactions by Block Range" endpoint moved to Pro plans.
Future focus: Etherscan will continue expanding AI agent infrastructure, emphasizing verified on-chain data delivery to AI systems, while optimizing multichain API services and tiered access strategies.
Matthew Tan is the founder and CEO of Etherscan. He previously founded Blockscan, an early token-based blockchain explorer for Counterparty. With around 15 years of experience in consulting and developing bespoke business solutions, he also serves as an advisor for blockchain and venture projects. He holds an MBA and a BSc in Computer Science from the University of Central Oklahoma.