Astronomical data discovery often requires identifying appropriate archives, resolving astronomical object names and coordinates, translating observational constraints into service-specific query parameters, and interpreting complex metadata returned by heterogeneous data services. Although the Astroquery Python package provides programmatic access to many astronomical archives, coordinating these resources still requires detailed knowledge of individual interfaces. We present AstroAKD, a data-search agent developed within NASA IMPACT’s Accelerated Knowledge Discovery (AKD) ecosystem, a modular platform for developing, evaluating, and deploying scientific AI agents that connect natural-language reasoning with external data and software services.

AstroAKD employs a Model Context Protocol (MCP) server built on Astroquery that dynamically exposes supported archive functions to a large language model (LLM) agent. At runtime, the agent discovers available functions, inspects their parameters, converts structured requests into astronomy-specific objects such as coordinates and unit-bearing quantities, and normalizes returned tables and metadata into machine-readable responses. Supported services include SIMBAD, ADS, MAST, HEASARC, IRSA, NED, Gaia, VizieR, and Virtual Observatory resources.

Given a scientific request, AstroAKD resolves target identifiers, extracts observational constraints, selects appropriate services, constructs executable queries, and returns relevant metadata and candidate datasets with archive provenance. We describe the agent architecture and evaluate representative single- and multi-archive workflows using archive and function selection, parameter correctness, task completion, and recovery from ambiguous identifiers, empty results, and unavailable services. Benchmark requests, tool calls, and outputs are retained as inspectable traces for validation and repeatability. AstroAKD demonstrates how domain-specific AI agents and standardized tool interfaces can support transparent, rapid exploration of astronomical archives.