Overview
The NASA MCP Server is a Model Context Protocol (MCP) server that provides programmatic access to NASA's public APIs, including Astronomy Picture of the Day (APOD), Mars Rover Images, Near Earth Objects (NEO) data, Earth imagery from EPIC, and Global Imagery Browse Services (GIBS). It also offers GIBS layers information and an Image Analysis Tool that fetches images from URLs, performs automatic format detection, compression, resizing, and base64 conversion for seamless LLM integration. Endpoints support parameterized queries such as APOD by date or range, Mars rover images by Earth date, sol, and camera; NEO feeds by date ranges with per-day limits; EPIC imagery by date and type; and GIBS imagery by layer, bbox, date, and output format. The server emphasizes error handling for invalid dates, network timeouts, API keys, and NASA-specific errors, and includes a comprehensive test suite. Setup instructions include installation via pip or uvx and configuring NASA API keys in VS Code or Claude Desktop environments.
Features
Astronomy Picture of the Day (APOD)
Access daily NASA APOD images with descriptions, including date-based retrieval and ranges.
Mars Rover Images
Retrieve Mars rover photos with configurable earth date, sol, and camera parameters.
Near Earth Objects (NEO)
Fetch asteroid data and close-approach information for specified date ranges.
Earth Images (EPIC)
Get satellite Earth images from NASA's DSCOVR EPIC, with date-based options and image type control.
GIBS Satellite Imagery
Access high-resolution Earth imagery via GIBS with layer, bbox, date, size, and format controls.
GIBS Layers Information
Retrieve metadata for all available GIBS imagery layers.
Image Analysis Tool
Fetch images from URLs, automatically detect format, compress/resize, and return base64-encoded content for LLMs.
Who Is This For?
- Developers:Build MCP-enabled apps that need ready access to NASA imagery APIs and image data.
- Data Scientists:Experiment with NASA imagery data retrieval and preprocessing for analyses and models.
- LLM/AI Researchers:Prepare base64-encoded images and prompts for model-based analysis and reasoning.
