The IP Geolocation MCP Server is a valuable tool within the MCP ecosystem, providing AI models with the ability to understand the geographic context of users based on their IP address. This server leverages the ipinfo.io API to deliver detailed information, including location, organization, and country. By integrating this server, AI models can personalize responses, tailor content, or implement location-based security measures.

The server's core functionality revolves around the get_ip_details tool, which accepts an IP address as input and returns comprehensive details via a Pydantic model. This allows for seamless integration with AI models through standard input/output or HTTP/SSE. To use this server, an IPInfo API token is required, ensuring secure and authorized access to geolocation data. This server empowers developers to create more context-aware and responsive AI applications.

IP Geolocation Enrichment

The core function of mcp-server-ipinfo is to enrich AI model context by providing geolocation data associated with IP addresses. When an AI model receives an IP address as input, this server leverages the ipinfo.io API to retrieve detailed information, including the city, region, country, organization, and postal code associated with that IP. This process allows the AI to understand the geographical context of the user or data source, enabling location-aware responses and actions. For example, an AI assistant could use this information to provide localized weather updates, suggest nearby restaurants, or tailor content based on the user's location. The server acts as a bridge, translating IP addresses into meaningful geographical insights for the AI model.

Dynamic Content Personalization

mcp-server-ipinfo enables dynamic content personalization within AI applications. By identifying the user's location through their IP address, the AI can customize the content it delivers. Imagine an e-commerce platform using an AI to recommend products; with IP-based geolocation, the AI can prioritize items that are popular or relevant in the user's specific region. Similarly, a news aggregator could use this information to highlight local news stories or events. This functionality enhances user engagement by providing a more relevant and personalized experience. The server facilitates this by providing the AI with the necessary location data, allowing it to make informed decisions about content delivery.

Threat Detection Augmentation

This MCP server can augment threat detection capabilities for AI-powered security systems. By correlating IP addresses with geographical locations and network information, the AI can identify potentially malicious activities. For instance, if multiple login attempts originate from disparate geographical locations within a short timeframe, it could indicate a compromised account. The server provides the AI with the necessary context to assess the risk associated with specific IP addresses, enhancing the accuracy and effectiveness of threat detection systems. This is particularly useful in scenarios where identifying the origin of network traffic is crucial for security analysis. The server acts as a real-time intelligence source, feeding location-based insights to the AI for security decision-making.

Technical Implementation

The mcp-server-ipinfo is implemented in Python and utilizes the ipinfo.io API to fetch IP address details. It defines a Pydantic model, IPDetails, to structure the output format, ensuring consistent data delivery to the AI model. The server interacts with AI models through standard input/output (stdio) or HTTP/SSE, offering flexibility in deployment and integration. To use the server, an IPINFO_API_TOKEN environment variable must be set, which is obtained from ipinfo.io after creating an account. The server exposes a get_ip_details tool that accepts an IP address as input and returns an IPDetails object containing the location, organization, and country details. This tool is the primary interface for AI models to access IP geolocation information.