Etherscan Api MCP server — 71 tools for AI agent integration. Hosted by Junct.
Connect Etherscan to Claude, Cursor or any other MCP client and it stops being a tab you switch to. Etherscan Api MCP server — 71 tools for AI agent integration. Hosted by Junct. The etherscan mcp server is what makes that connection.
Hosted at etherscan-api.mcp.junct.dev/mcp. Free to use. No auth. No API key required.
This MCP server is deterministically generated from the Etherscan API specification. Every tool maps 1:1 to a real API endpoint — no hallucinated endpoints.
The toolset is worth reading before you wire it up, because it tells you what the integration is really for:
Protocol — ** EtherscanEndpoint — ** https://etherscan-api.mcp.junct.dev/mcpTransport — ** Streamable HTTPAuth — ** None requiredDocumentation — ** etherscan-api.mcp.junct.dev/llms.txtBecause this one is hosted, setup is mostly authentication — you point your client at the endpoint and approve access. Nothing runs on your machine, so there is no runtime to keep patched.
This sits in the knowledge and memory group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Etherscan's toolset — Protocol, Endpoint, Transport and 2 more — is a fair guide to whether it matches your workflow. It is maintained by junct-bot; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against Etherscan's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
| Tool | What it does |
|---|---|
| Protocol | ** Etherscan |
| Endpoint | ** https://etherscan-api.mcp.junct.dev/mcp |
| Transport | ** Streamable HTTP |
| Auth | ** None required |
| Documentation | ** [etherscan-api.mcp.junct.dev/llms.txt](https://etherscan-api.mcp.junct.dev/llms.txt) |
{
"mcpServers": {
"etherscan-api": {
"url": "https://etherscan-api.mcp.junct.dev/mcp",
"transport": "streamable-http"
}
}
}Configuration as documented by the project. Restart the client after saving.
A knowledge graph your assistant keeps between sessions — entities, relations and observations that persist.
Kill hallucinated APIs — version-accurate, up-to-date library documentation injected straight into context.
Your workspace, on speaking terms with AI — search, read and write Notion pages and databases.
A structured scratchpad for hard problems — stepwise reasoning with revisions, branches and visible logic.
Symbol-level code navigation, refactoring and memory for coding agents — the IDE brain your assistant has been missing.
Chat with your second brain — search, read and write vault notes through the Local REST API.