Shodan MCP Server Overview

The Shodan MCP Server bridges the powerful network‑search capabilities of Shodan with AI assistants that understand the Model Context Protocol (MCP). By exposing a set of well‑defined tools, it allows developers to embed real‑time device intelligence, vulnerability data, and domain resolution directly into conversational AI workflows. This eliminates the need to manually query Shodan’s REST API, parse JSON responses, or handle authentication in each application.

At its core, the server offers five primary tools: , , , , and . Each tool accepts a concise JSON payload, performs the corresponding Shodan query, and returns structured data that can be consumed by an AI assistant. For example, retrieves comprehensive host details—open ports, services, and location—while lets users run complex Shodan search strings to discover devices matching arbitrary criteria. This level of granularity gives developers fine control over the data they request, ensuring that AI agents can provide precise answers or trigger downstream actions.

The value for developers lies in seamless integration. Once the MCP server is registered in an AI’s configuration, a single call to yields the desired information. This pattern supports both synchronous and asynchronous workflows, enabling real‑time threat hunting, automated incident response, or continuous monitoring dashboards. Because the server handles authentication via environment variables and respects MCP’s auto‑approval semantics, it fits naturally into existing security policies without exposing API keys to the client side.

Real‑world use cases abound: a security analyst can ask an AI assistant, “What vulnerabilities are present on the device at 192.168.1.10?” and receive a list of CVEs without leaving the chat; a DevOps engineer can query to validate domain resolution before deploying services; or a researcher might use with advanced filters (e.g., “port:22 country:US”) to map SSH‑enabled hosts worldwide. In each scenario, the MCP server eliminates boilerplate code and ensures consistent data formatting across tools.

Unique advantages of this implementation include a lightweight TypeScript codebase that compiles to Node.js, straightforward configuration via the standard MCP settings file, and an open‑source license that encourages community contributions. By encapsulating Shodan’s rich dataset behind MCP, the server empowers AI assistants to deliver actionable intelligence while keeping developers focused on higher‑level logic rather than API intricacies.