IP2Location.io MCP Server

The IP2Location.io MCP server bridges the gap between conversational AI assistants and real‑world network data by exposing the IP2Location.io geolocation API through the Model Context Protocol. Developers and AI users can now ask a model questions such as “Where is 8.8.8.8 located?” or “What ISP does IP 2001:4860:4860::8888 belong to?” and receive a structured, machine‑readable response without leaving the chat interface. This eliminates the need for manual API calls or custom integrations, streamlining workflows that require location intelligence.

At its core, the server accepts an IP address and returns a rich JSON payload that includes country, region, city, latitude, longitude, ZIP code, time zone, and even network details like ASN, ISP, domain, and proxy status. By providing both geographic and security insights—such as whether the address is behind a known proxy—the tool empowers applications that need to verify user authenticity, tailor content to regional regulations, or detect malicious traffic patterns. The data is fetched asynchronously using , ensuring that AI assistants remain responsive even when the server processes multiple concurrent requests.

Key capabilities of this MCP server are:

• Broad data coverage: From basic location fields to advanced network and security metrics.
• Flexible access tiers: Free usage without an API key (1 000 queries/day) and a paid tier that lifts the limit to 50 000 queries/month, making it suitable for both experimentation and production workloads.
• Seamless integration: Implemented as a tool, it can be added to any MCP‑compatible client with minimal configuration.
• Asynchronous request handling: Non‑blocking calls keep the assistant’s dialogue flow smooth, even under heavy load.

Typical use cases include:

• Compliance and localization: Automatically adjusting content or services based on the user’s country or region.
• Security and fraud detection: Flagging traffic that originates from known proxies, VPNs, or suspicious ASNs.
• Analytics and reporting: Aggregating geolocation data to visualize user distribution or network performance across regions.
• Developer tooling: Providing quick IP lookup capabilities within IDEs, chatbots, or monitoring dashboards.

By integrating this MCP server into AI workflows, developers gain a powerful, ready‑to‑use geolocation service that scales with their needs. The server’s design—leveraging the MCP framework, asynchronous I/O, and a clear API contract—ensures that it can be dropped into existing AI ecosystems with minimal friction, delivering actionable network intelligence directly to the assistant’s conversational context.