# Etherscan

> Use this tool when you need to access and analyze Ethereum blockchain data, such as checking ETH balances, tracking transactions, or monitoring gas prices. It provides a seamless interface for AI assistants to fetch contract ABIs, resolve ENS names, and view transaction histories through Etherscan's API. Ideal for use cases where blockchain data analysis is required within a conversation interface.

Canonical page: https://skillsregistry.net/skills/etherscan  
JSON: https://api.skillsregistry.net/v1/skills/etherscan

## Description

MCP Etherscan Server provides Ethereum blockchain data tools through Etherscan's API, enabling AI assistants to check ETH balances, view transaction histories, track ERC20 transfers, fetch contract ABIs, monitor gas prices, and resolve ENS names. Built with TypeScript and the Model Context Protocol SDK, it runs on stdio transport for seamless integration with Claude Desktop, making it particularly valuable for users who need to access and analyze blockchain data without leaving their conversation interface.

## Trust

- **Trust score (0–1):** 0.98
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** finance
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/etherscan)
- **Repository:** <https://github.com/otc-ai/mcp-otc>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "etherscan"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/etherscan` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/etherscan/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt