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ZoomEye MCP Server

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πŸš€ 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.

πŸ”” Announcement

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

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

πŸ” Search global internet assets, track real-time changes, and unlock AI-driven insights β€” all in one place.

πŸ‘‰ 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 β€” explore the power of AI asset search today!

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

πŸ”§ Fully compatible with leading MCP environments:

  • Claude Desktop

  • Cursor

  • Windsurf

  • Cline

  • Continue

  • Zed

  • Cherry Studio

  • Chatbox

πŸ”— Explore ZoomEye MCP Server on:

We welcome everyone to use, explore, and contribute!

Related MCP server: Shodan-MCP-Server

πŸ”‘ 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.ai

  2. Register or log in

  3. Click your avatar β†’ 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-server-zoomeye via pip:

pip install mcp-server-zoomeye

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

python -m mcp_server_zoomeye

Using Docker

You can also run the ZoomEye MCP server using Docker:

Pull from Docker Hub

# Pull the latest image
docker pull zoomeyeteam/mcp-server-zoomeye:latest

# Run the container with your API key
docker run -i --rm -e ZOOMEYE_API_KEY=your_api_key_here zoomeyeteam/mcp-server-zoomeye:latest

Note: We provide multi-architecture Docker images that support linux/amd64 and linux/arm64 platforms and can run on Intel/AMD and ARM (such as Apple Silicon) processors.

Build from Source

Alternatively, you can build the Docker image from source:

# Clone the repository
git clone https://github.com/zoomeye-ai/mcp_zoomeye.git
cd mcp_zoomeye

# Build the Docker image
docker build -t zoomeyeteam/mcp-server-zoomeye:local .

# Run the container
docker run -i --rm -e ZOOMEYE_API_KEY=your_api_key_here zoomeyeteam/mcp-server-zoomeye:local

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 mcp-server-zoomeye

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 mcp-server-zoomeye

# Or create and install in a new virtual environment
uv venv
uv pip install mcp-server-zoomeye

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"

  2. Pass directly when running the container (for Docker):

    docker run -i --rm -e ZOOMEYE_API_KEY=your_api_key_here zoomeyeteam/mcp-server-zoomeye:latest

Configure Claude.app

Add the following in Claude settings:

"mcpServers": {
  "zoomeye": {
    "command": "uvx",
    "args": ["mcp-server-zoomeye"],
    "env": {
        "ZOOMEYE_API_KEY": "your_api_key_here"
    }
  }
}
"mcpServers": {
  "zoomeye": {
    "command": "docker",
    "args": ["run", "-i", "--rm", "-e", "ZOOMEYE_API_KEY=your_api_key_here", "zoomeyeteam/mcp-server-zoomeye:latest"],
    "env": {
      "ZOOMEYE_API_KEY": "your_api_key_here"
    }
  }
}
"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:

"context_servers": [
  "mcp-server-zoomeye": {
    "command": "uvx",
    "args": ["mcp-server-zoomeye"],
    "env": {
        "ZOOMEYE_API_KEY": "your_api_key_here"
    }
  }
],
"context_servers": {
  "mcp-server-zoomeye": {
    "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 mcp-server-zoomeye

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

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 mcp-server-zoomeye 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 mcp-server-zoomeye more robust and practical.

License

mcp-server-zoomeye 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.

Available Tools

3 tools
zoomeye_vuldb_by_idC

Search for detailed vulnerability information by vulnerability ID and return formatted results.

Use this tool to retrieve comprehensive security vulnerability details from the vulnerability
database using a vulnerability identifier (CVE, CNVD, CNNVD). Results include:
ParametersJSON Schema
NameRequiredDescriptionDefault
cve_idYesA valid vulnerability identifier, eg: CVE-XXXX-XXXX,CNVD-XXXX-XXXX,CNNVD-XXXX-XXXX

TDQS

C2.6/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description must fully disclose behavioral traits. It indicates a read-only operation (search/retrieve), but fails to describe output format, pagination, rate limits, or any side effects. The abrupt end ('Results include:') leaves the agent guessing what the tool returns, which is a significant gap for transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short, but it is incomplete, ending with 'Results include:' without any continuation. This disrupts the structure and leaves the description unfinished. Every sentence should be complete and purposeful, and this one fails to deliver its intended content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description should explain the return values comprehensively. It starts listing results but cuts off, providing zero information about what the formatted results contain. This is a major omission for a tool that only has one parameter and no other documentation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% coverage, with the parameter 'cve_id' described and examples given. The description repeats this information without adding substantial new meaning. Baseline is 3, and since no extra semantics are provided, the score remains at 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Search for detailed vulnerability information by vulnerability ID', specifying the verb and resource. It lists the accepted ID formats (CVE, CNVD, CNNVD), which helps the agent understand the tool's scope. However, it does not differentiate from sibling tools like 'zoomeye_search' or 'zoomeye_vuldb_by_keyword', and the incomplete sentence 'Results include:' slightly reduces clarity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description says 'Use this tool to retrieve...' but provides no guidance on when to use it versus alternatives, such as the sibling tool 'zoomeye_vuldb_by_keyword'. There is no mention of prerequisites, limitations, or exclusions, leaving the agent to infer usage context without explicit advice.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

zoomeye_vuldb_by_keywordA

Search ZoomEye's vulnerability database for security vulnerabilities based on a specified keyword.

This function queries the ZoomEye vulnerability database to retrieve information about known security vulnerabilities associated with specific products, vendors. Results include vulnerability details such as CVE IDs, severity ratings, affected versions, and vulnerability descriptions.

ParametersJSON Schema
NameRequiredDescriptionDefault
keywordYesSearch term to query the vulnerability database. This can be a product name, vendor name (e.g., "nginx", "mysql", "tomcat", "WordPress", "hikvision", "huawei").
page_sizeNoNumber of records per page, default is 10, maximum is 100.

TDQS

A3.7/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, but the description only lists output fields without behavioral disclosures like read-only guarantee, rate limits, or authentication needs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded, though the second paragraph could be shortened without losing value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description reasonably explains return fields (CVE, severity, etc.) and implies pagination via page_size, though total count is omitted.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and the description enhances understanding by providing examples for keyword and clarifying page_size defaults/maximum.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches ZoomEye's vulnerability database by keyword, and implicitly distinguishes it from siblings (search vs. by ID).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains it retrieves vulnerability info for products/vendors but does not explicitly compare with zoomeye_search or zoomeye_vuldb_by_id.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.4/5.0
Disambiguation5/5

Each tool serves a distinct purpose: one for general asset search, one for vulnerability detail by ID, and one for vulnerability keyword search. There is no overlap in functionality.

Naming Consistency5/5

All tools follow a consistent 'zoomeye_' prefix with snake_case naming: search, vuldb_by_id, vuldb_by_keyword. Pattern is uniform and predictable.

Tool Count4/5

With 3 tools, the set is minimal but appropriate for the ZoomEye domain, covering asset search and vulnerability queries. Slightly thin but reasonable given the focused scope.

Completeness3/5

The tools cover basic search and vulnerability lookup, but lack features like retrieving detailed host info, filtering by specific fields, or obtaining result counts. Some operations are missing for full workflow coverage.

Maintenance

ActivityInactive
ResponsivenessSyncing

Resources

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