Transforms ALMA (Atacama Large Millimeter/submillimeter Array) archive queries into natural language conversations, providing seamless access to astronomical data.
Sponsored
The ALMA Model Context Protocol (MCP) server revolutionizes how researchers interact with the vast ALMA archive by converting complex data queries into intuitive natural language conversations. It eliminates the need for users to master intricate TAP/ADQL syntax or specific archive APIs, instead allowing them to simply ask for the data they need and receive analysis-ready results. This architecture is designed to empower AI assistants and other LLMs to effortlessly search ALMA data by various criteria such as target, position, frequency, resolution, proposal details, or any custom parameters, making astronomical data access more accessible and efficient.
主要功能
010 GitHub stars
02Natural Language Query Interface for ALMA Data
03Comprehensive ALMA Archive Access (Target, Position, Frequency, Resolution, Proposal)
04Support for Custom ADQL/SQL Queries against the ALMA TAP
05Spectral Line Coverage and Sensitivity-Based Searches
06Multi-Backend Integration with alminer, pyvo, and astroquery
使用案例
01Enable AI assistants to search the ALMA archive for specific astronomical observations using natural language.
02Allow researchers to query ALMA data by target, frequency, or resolution without writing complex code.
03Integrate ALMA data retrieval capabilities into larger LLM-based scientific workflows and tools.