# ZoomEye

> Use this tool when you need to retrieve network asset information for cybersecurity workflows, such as network reconnaissance, and integrate it into AI assistant conversations. It solves problems related to global network asset searching, filtering, and data retrieval through a specialized API query interface. The tool takes in API keys and search queries as input and outputs relevant network asset data, making it ideal for use cases requiring automated network discovery and analysis.

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

## Description

The ZoomEye MCP Server provides network asset information to LLMs through a set of specialized tools that query the ZoomEye API. Developed by zoomeye.ai, this Python implementation enables searching for global network assets using dorks, with support for filtering by IP version, pagination, and specific field selection. The server features caching to improve performance, automatic retry mechanisms for failed API requests, and comprehensive error handling. It can be deployed via Docker, pip installation, or run directly with uv, requiring only a ZoomEye API key for authentication. This implementation is particularly valuable for cybersecurity workflows requiring network reconnaissance capabilities within AI assistant conversations.

## Trust

- **Trust score (0–1):** 0.64
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** cloud-infra
- **Updated:** 2026-09-01

## Source

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

## 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": "zoomeye"
    }
  }
}
```

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