What are the runtime requirements?
Node.js version 16 or higher and internet access to `https://api.zoomeye.org`. You also need a valid ZoomEye API key, obtainable from your ZoomEye profile page.
@help116114
基本情報
ZoomEye MCP Server - 网络资产搜索与用户信息查询
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"zoomeye": {
"command": "node",
"args": [
"./build/index.js"
],
"env": {
"ZOOMEYE_API_KEY": ""
}
}
}
}ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
Zoomeye MCP Server is an MCP (Model Context Protocol) server that provides access to the ZoomEye v2 API, enabling AI assistants to query internet‑wide host and web data, view account quotas, and (for paid plans) fetch IP history. It is built for developers and security researchers who want to integrate ZoomEye cyberspace search capabilities into MCP‑compatible AI tools.
Clone the repository, install dependencies with npm install, build with npm run build, export your Zoomeye API key as ZOOMEYE_API_KEY, and start the server with npm start. For integration with MCP‑compatible LLMs (e.g., Cline, Cursor, Claude), add the server configuration to your MCP settings file, specifying the build path and API key.
Node.js version 16 or higher and internet access to `https://api.zoomeye.org`. You also need a valid ZoomEye API key, obtainable from your ZoomEye profile page.
The server expects the ZoomEye API key to be set in the `ZOOMEYE_API_KEY` environment variable (or exported before starting). This key is used for all requests to the ZoomEye API.
Yes. Some Zoomeye API endpoints require a paid membership. According to the README, features such as IP history (`get_history_ip`), search functionality, network scanning, SSL certificate lookup, and IoT device search are only available with a paid ZoomEye API key.
All data comes from the ZoomEye v2 API. The server does not store any data locally; it queries ZoomEye’s cloud database on behalf of the AI assistant.
Many tools accept optional `max_items` (default 5) and `fields` parameters to control the number of items and which fields are returned. The summarization tool also defaults to 5 items.

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