Overview

The MCP Demo Server provides a lightweight, ready‑to‑run bridge between Claude and NASA’s Near‑Earth Object (NEO) API. It solves the problem of exposing external REST services to an AI assistant in a way that is both secure and developer‑friendly. By encapsulating the NEO API behind an MCP server, developers can query asteroid data directly from Claude without handling authentication tokens or crafting HTTP requests themselves. This abstraction is particularly valuable for teams building scientific tools, educational apps, or real‑time monitoring dashboards that rely on up‑to‑date celestial information.

At its core, the server implements a single tool, , which accepts a date range and returns NEO data for that interval. The tool is exposed through the MCP protocol, so Claude can invoke it using a simple JSON payload. Underneath the hood the server reads an API key from , making it trivial to swap keys or add additional authentication mechanisms. The MCP Inspector, a built‑in debugging interface, lets developers watch the request flow and inspect responses in real time, greatly easing integration testing.

Key capabilities include:

• API key management – store and use a NASA API key securely within the server environment.
• Date‑range querying – specify start and end dates to retrieve all NEOs observed during that period.
• MCP Inspector – a live proxy dashboard that logs tool calls, responses, and performance metrics.
• CLI tooling – commands such as , , and streamline deployment, local development, and integration with the Claude desktop app.

Typical use cases span educational platforms that display asteroid trajectories, research pipelines that need bulk NEO data for statistical analysis, and hobbyist projects that visualize near‑earth objects on a map. By embedding the server into an AI workflow, Claude can answer questions like “Which asteroids were closest to Earth in March 2024?” or “Show me all NEOs between two dates,” and immediately pass the structured data back to the user or downstream services.

What sets this MCP server apart is its minimal footprint and focus on a single, high‑value API. The design allows developers to quickly spin up the service with , configure it in Claude’s settings, and start querying without writing any custom code. This plug‑and‑play model accelerates the integration of external scientific data into conversational AI applications, making complex datasets accessible through natural language interactions.