Skip to main content

🚀 ZoomEye MCP Server

A Model Context Protocol (MCP) server that provides network asset information based on query conditions. This server allows Large Language Models (LLMs) to obtain network asset information by querying ZoomEye using dorks and other search parameters.

🔔 Announcement

🎉 We are excited to announce the official open-source release of ZoomEye MCP Server — a powerful Model Context Protocol (MCP) server that brings real-time cyber asset intelligence to AI assistants and development environments.

🚀 Free Trial: 7-Day FREE Access to ZoomEye MCP! Experience ZoomEye MCP — the AI-powered cyberspace asset search engine — absolutely free for 7 days!

🔍 Search global internet assets, track real-time changes, and unlock AI-driven insights — all in one place.

👉 How to claim:

  1. Follow us on Twitter: @zoomeye_team
  2. DM us "MCP" and your MCP setup screenshot
  3. Get instant access to your 7-day membership

🎁 Limited-time free trial — explore the power of AI asset search today!

💡 Provide insightful feedback that gets officially adopted, and you'll unlock even more rewards!

🔧 Fully compatible with leading MCP environments:

  • Claude Desktop
  • Cursor
  • Windsurf
  • Cline
  • Continue
  • Zed
  • Cherry Studio
  • Chatbox

🔗 Explore ZoomEye MCP Server on:

We welcome everyone to use, explore, and contribute!

🔑 How can I get a ZoomEye API key?

To use this MCP server, you’ll need a ZoomEye API key.

  1. Go to https://www.zoomeye.org

  2. Register or log in

  3. Click your avatar → Profile

  4. Copy your API-KEY

  5. Set the environment variable:

    export ZOOMEYE_API_KEY="your_api_key_here"

zoomeye1

zoomeye2

Features

  • Query ZoomEye for network asset information using dorks
  • Caching mechanism to improve performance and reduce API calls
  • Automatic retry mechanism for failed API requests
  • Comprehensive error handling and logging

Available Tools

  • zoomeye_search - Get network asset information based on query conditions.
    • Required parameters:
      • qbase64 (string): Base64 encoded query string for ZoomEye search
    • Optional parameters:
      • page (integer): View asset page number, default is 1
      • pagesize (integer): Number of records per page, default is 10, maximum is 1000
      • fields (string): The fields to return, separated by commas
      • sub_type (string): Data type, supports v4, v6, and web. Default is v4
      • facets (string): Statistical items, separated by commas if there are multiple
      • ignore_cache (boolean): Whether to ignore the cache

Usage Guide

Basic Usage

Once the server is running, you can interact with it through your AI assistant or development environment. Here's how to use it:

  1. Start the server using one of the installation methods above
  2. Configure your AI assistant (Claude Desktop, Cursor, Windsurf, Cline, Continue, Zed, etc.) to use the server
  3. Query network information using natural language

searchexample

Search Syntax Guide

  • Search Scope covers devices (IPv4, IPv6) and websites (domains).
  • When entering a search string, the system will match keywords in "global" mode, including content from various protocols such as HTTP, SSH, FTP, etc. (e.g., HTTP/HTTPS protocol headers, body, SSL, title, and other protocol banners).
  • Search strings are case-insensitive and will be segmented for matching (the search results page provides a " segmentation" test feature). When using == for search, it enforces exact case-sensitive matching with strict syntax.
  • Please use quotes for search strings (e.g., "Cisco System" or 'Cisco System'). If the search string contains quotes, use the escape character, e.g.,"a"b". If the search string contains parentheses, use the escape character, e.g., portinfo().

You can see more detailed search syntax rules in prompts.py.

For more information on the ZoomEye Search API, refer to the ZoomEye API v2 documentation.

Getting Started

Prerequisites

  1. ZoomEye API Key

    • Register for an account at ZoomEye
    • Obtain your API key from your account settings
    • The API key will be used to authenticate your requests to the ZoomEye API
  2. Python Environment

    • Python 3.10 or higher is required
    • Alternatively, you can use Docker to run the server without installing Python

Installation

Using PIP

Alternatively, you can install mcp-zoomeye-org via pip:

pip install mcp-zoomeye-org

After installation, you can run it as a script using the following command:

python -m mcp_zoomeye_org

Using uv

uv is a fast Python package installer and resolver written in Rust. It's a modern alternative to pip that offers significant performance improvements.

Installation of uv

# Install uv using curl (macOS/Linux)
curl -LsSf https://astral.sh/uv/install.sh | sh

# Or using PowerShell (Windows)
irm https://astral.sh/uv/install.ps1 | iex

# Or using Homebrew (macOS)
brew install uv

Using uvx to run mac-zoomeye-org

No specific installation is required when using uvx, which allows you to run Python packages directly:

Installing with uv

Alternatively, you can install the package using uv:

# Install in the current environment
uv pip install mac-zoomeye-org

# Or create and install in a new virtual environment
uv venv
uv pip install mac-zoomeye-org

Configuration

Environment Variables

The ZoomEye MCP server requires the following environment variable:

  • ZOOMEYE_API_KEY: Your ZoomEye API key for authentication

You can set this environment variable in several ways:

  1. Export in your shell session:

    export ZOOMEYE_API_KEY="your_api_key_here"
    

Configure Claude.app

Add the following in Claude settings:

Using uvx
"mcpServers": {
  "zoomeye": {
    "command": "uvx",
    "args": ["mac-zoomeye-org"],
    "env": {
        "ZOOMEYE_API_KEY": "your_api_key_here"
    }
  }
}
Installed via pip
"mcpServers": {
  "zoomeye": {
    "command": "python",
    "args": ["-m", "mcp_server_zoomeye"],
    "env": {
        "ZOOMEYE_API_KEY": "your_api_key_here"
    }
  }
}

Configure Zed

Add the following in Zed's settings.json:

Using uvx
"context_servers": [
  "mac-zoomeye-org": {
    "command": "uvx",
    "args": ["mac-zoomeye-org"],
    "env": {
        "ZOOMEYE_API_KEY": "your_api_key_here"
    }
  }
],
Installed via pip
"context_servers": {
  "mac-zoomeye-org": {
    "command": "python",
    "args": ["-m", "mcp_server_zoomeye"],
    "env": {
        "ZOOMEYE_API_KEY": "your_api_key_here"
    }
  }
},

Example Interactions

Example 1: Retrieve global Apache Tomcat assets

{
  "name": "zoomeye_search",
  "arguments": {
    "qbase64": "app=\"Apache Tomcat\""
  }
}

Response:

{
  "code": 60000,
  "message": "success",
  "total": 163139107,
  "query": "app=\"Apache Tomcat\"",
  "data": [
    {
      "url": "https://1.1.1.1:443",
      "ssl.jarm": "29d29d15d29d29d00029d29d29d29dea0f89a2e5fb09e4d8e099befed92cfa",
      "ssl.ja3s": "45094d08156d110d8ee97b204143db14",
      "iconhash_md5": "f3418a443e7d841097c714d69ec4bcb8",
      "robots_md5": "0b5ce08db7fb8fffe4e14d05588d49d9",
      "security_md5": "0b5ce08db7fb8fffe4e14d05588d49d9",
      "ip": "1.1.1.1",
      "domain": "www.google.com",
      "hostname": "SPACEX",
      "os": "windows",
      "port": 443,
      "service": "https",
      "title": ["GoogleGoogle appsGoogle Search"],
      "version": "1.1.0",
      "device": "webcam",
      "rdns": "c01031-001.cust.wallcloud.ch",
      "product": "OpenSSD",
      "header": "HTTP/1.1 302 Found Location: https://www.google.com/?gws_rd=ssl Cache-Control: private...",
      "header_hash": "27f9973fe57298c3b63919259877a84d",
      "body": "HTTP/1.1 302 Found Location: https://www.google.com/?gws_rd=ssl Cache-Control: private...",
      "body_hash": "84a18166fde3ee7e7c974b8d1e7e21b4",
      "banner": "SSH-2.0-OpenSSH_7.6p1 Ubuntu-4ubuntu0.3",
      "update_time": "2024-07-03T14:34:10",
      "header.server.name": "nginx",
      "header.server.version": "1.8.1",
      "continent.name": "Europe",
      "country.name": "Germany",
      "province.name": "Hesse",
      "city.name": "Frankfurt",
      "lon": "118.753262",
      "lat": "32.064838",
      "isp.name": "aviel.ru",
      "organization.name": "SERVISFIRST BANK",
      "zipcode": "210003",
      "idc": 0,
      "honeypot": 0,
      "asn": 4837,
      "protocol": "tcp",
      "ssl": "SSL Certificate Version: TLS 1.2 CipherSuit: TLS_ECDHE_RSA_WITH_AES_128_GCM_SHA256...",
      "primary_industry": "Finance",
      "sub_industry": "bank",
      "rank": 60
    }
  ]
}

Debugging and Troubleshooting

Using MCP Inspector

The Model Context Protocol Inspector is a tool that helps debug MCP servers by simulating client interactions. You can use it to test your ZoomEye MCP server:

# For uvx installation
npx @modelcontextprotocol/inspector uvx mac-zoomeye-org

# If developing locally
cd path/to/servers/src/mcp_server_zoomeye
npx @modelcontextprotocol/inspector uv run mac-zoomeye-org

Common Issues

  1. Authentication Errors

    • Ensure your ZoomEye API key is correct and properly set as an environment variable
    • Check that your API key has not expired or been revoked
  2. Connection Issues

    • Verify your internet connection
    • Check if the ZoomEye API is experiencing downtime
  3. No Results

    • Your query might be too specific or contain syntax errors
    • Try simplifying your query or using different search terms
  4. Rate Limiting

    • ZoomEye API has rate limits based on your account type
    • Space out your requests or upgrade your account for higher limits

Advanced Usage

Caching

The ZoomEye MCP server implements caching to improve performance and reduce API calls:

  • Responses are cached based on the query parameters
  • Cache duration is configurable (default: 1 hour)
  • You can bypass the cache by setting ignore_cache to true in your query

Custom Fields

You can request specific fields in your query results by using the fields parameter:

{
  "name": "zoomeye_search",
  "arguments": {
    "qbase64": "app=\"Apache\"",
    "fields": "ip,port,domain,service,os,country,city"
  }
}

Pagination

For queries that return many results, you can paginate through them:

{
  "name": "zoomeye_search",
  "arguments": {
    "qbase64": "app=\"Apache\"",
    "page": 2,
    "pagesize": 20
  }
}

Contributing

We encourage contributions to mac-zoomeye-org to help expand and improve its functionality. Whether it's adding new related tools, enhancing existing features, or improving documentation, your input is valuable.

For examples of other MCP servers and implementation patterns, see: https://github.com/modelcontextprotocol/servers

Pull requests are welcome! Feel free to contribute new ideas, bug fixes, or enhancements to make mac-zoomeye-org more robust and practical.

License

mac-zoomeye-org is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more information, see the LICENSE file in the project repository.

Metadata

Release files for mcp-zoomeye-org 0.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for mcp-zoomeye-org 0.1.0
File Size Uploaded
mcp_zoomeye_org-0.1.0.tar.gz 1.4 MB Details

Built distribution (wheel)

Table of built distributions (wheels) for mcp-zoomeye-org 0.1.0
File Interpreter ABI Platform
mcp_zoomeye_org-0.1.0-py3-none-any.whl Python 3 none any Details

Total release size: 1.4 MB

Release files / mcp_zoomeye_org-0.1.0.tar.gz

Download URL mcp_zoomeye_org-0.1.0.tar.gz
Size 1.4 MB
Tags Source
SHA-256 checksum
How to use checksums
8e6f568164b1d592cd58ddc5d894c2caf9c839fe47e3af3139ca7317a8f143d1
BLAKE2b-256 checksum
How to use checksums
1dd16524cabce7fd37514e9f604e1b329cb45434263bb1167c68596183378927
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.12.0

Release files / mcp_zoomeye_org-0.1.0-py3-none-any.whl

Download URL mcp_zoomeye_org-0.1.0-py3-none-any.whl
Size 13.4 kB
Tags Python 3
SHA-256 checksum
How to use checksums
828a0ae426e6874e11fc4e5776d872a4a44aa6974e0ea8e197429ac93ff0cd72
BLAKE2b-256 checksum
How to use checksums
98fda325375b20a588bc5f4cdaadeb09bf528711f874c8113c088f91557792cc
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.12.0

Release history Release notifications | RSS feed

This release

0.1.0 This release

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page