Mcp Ip Geo

Overview

is a lightweight Model Context Protocol (MCP) server that exposes IP geolocation lookup services powered by ip-api.com. It transforms a simple HTTP request into structured geographic data—country, region, city, latitude, longitude, and more—allowing AI assistants to enrich conversations with location context without external dependencies. This is particularly valuable for developers who need quick, reliable IP resolution in a privacy‑preserving, serverless-friendly manner.

Solving a Common AI Integration Gap

Modern AI assistants often require contextual data about the user or environment. While many platforms offer built‑in location services, they can be limited by rate limits, cost, or licensing constraints. fills this gap by providing a dedicated MCP endpoint that any Claude or other AI client can query via the standard MCP protocol. By delegating geolocation to a single, well‑maintained service, developers avoid reinventing the wheel and can focus on higher‑level logic.

What It Does and Why It Matters

• Unified Geolocation API: The server translates an IP address into a JSON payload containing geographic details. This abstraction removes the need to handle raw HTTP calls or parse responses manually.
• MCP Compatibility: It adheres strictly to MCP’s resource and tool conventions, making it plug‑and‑play with existing AI workflows that support the protocol.
• Zero‑Configuration Docker: For containerized environments, a ready‑to‑run Docker image ensures consistent deployment across CI/CD pipelines or cloud platforms.
• Scalable and Stateless: Each request is independent, enabling horizontal scaling without shared state or complex orchestration.

Key Features

• Country, Region, City: Basic location identifiers suitable for content personalization or compliance checks.
• Geographic Coordinates: Latitude and longitude enable mapping, distance calculations, or integration with GIS services.
• Time Zone & ISP: Optional fields that add depth to user profiling or debugging sessions.
• Free Tier Support: Built on the free tier of ip-api.com, making it accessible for non‑commercial projects while offering a clear upgrade path to the paid plan for higher volume needs.

Real‑World Use Cases

• Chatbot Localization: A customer support bot can tailor responses based on the user’s city or region, improving relevance and compliance with local regulations.
• Fraud Detection: By correlating IP geolocation with transaction data, AI models can flag anomalous activity that occurs outside expected regions.
• Content Delivery Optimization: AI systems recommending streaming or download options can use location data to prioritize nearby servers, reducing latency.
• Compliance Auditing: Legal or privacy checks can automatically verify that data handling aligns with regional laws (e.g., GDPR, CCPA).

Integration Into AI Workflows

Developers configure the MCP client to point at via either a local executable or a Docker‑hosted endpoint. Once integrated, the assistant can invoke the geolocation tool by passing an IP address as a parameter; the MCP server returns structured data that the assistant can directly incorporate into prompts or downstream models. This seamless interaction eliminates manual API handling, reduces latency, and keeps the assistant’s codebase clean.

Standout Advantages

• Protocol‑First Design: By embracing MCP, the server guarantees compatibility with any AI platform that supports the protocol, future‑proofing deployments.
• Deployment Flexibility: Whether you prefer a lightweight Go binary or a Docker container, the server accommodates both environments without extra configuration.
• Cost‑Effective: Leveraging the free tier of ip-api.com keeps operational costs low for small projects, while still offering a clear upgrade path for commercial use.

In summary, provides developers with a ready‑made, protocol‑compliant geolocation service that can be effortlessly woven into AI assistants, enhancing context awareness and enabling richer user experiences without the overhead of managing external APIs.