ZoomEye
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.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-01.
Scan details: Circle-IR · 2026-09-01 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- cloud-infra
- Source
- PulseMCP
- Repository
- github.com/zoomeye-ai/mcp_zoomeye
- Author type
- human
- Last scanned
- 2026-09-01
- Updated
- 2026-09-01
Use via MCP
Resolve ZoomEye from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.