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NASA-PDS

NASA PDS Registry MCP Server

Official
by NASA-PDS

Search Collections

search_collections

Find NASA PDS data collections by instrument, target, instrument host, or investigation to locate planetary datasets for a mission or research need.

Instructions

Search PDS data collections filtered by instrument, target, instrument host, or investigation. Example: Mars Reconnaissance Orbiter HiRISE data collections targeting Mars.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results (default 10)
ref_lid_targetNoURN identifier for target (e.g. urn:nasa:pds:context:target:planet.mars)
ref_lid_instrumentNoURN identifier for instrument (e.g. urn:nasa:pds:context:instrument:mars2020.mastcamz)
ref_lid_investigationNoURN identifier for investigation (e.g. urn:nasa:pds:context:investigation:mission.mars2020)
ref_lid_instrument_hostNoURN identifier for instrument host (e.g. urn:nasa:pds:context:instrument_host:spacecraft.mars2020)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.2/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioral burden. It never states that this is a read-only lookup, how filters combine (AND vs OR), how the limit interacts with result sets, or any rate/auth constraints — 'search' implies read-only but nothing is disclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the purpose and followed by a single illustrative example; nothing is padded. The example sentence earns its place by grounding abstract filter names in a real query.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists so return values need no explanation, and all 0-required params are documented in the schema. However, for a 5-parameter search tool with five sibling search tools, the description omits filter-combination behavior, result-set size expectations, and routing guidance — leaving meaningful gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% with URN examples for each ref_lid_* parameter, so the schema already does the heavy lifting. The description's filter list mirrors the parameter names and adds no URN syntax or combination semantics beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource (search PDS data collections) and enumerates the four filter dimensions, which maps directly onto the schema. It is clearly distinguishable from siblings like search_investigations or search_targets, which operate on different context entity types, though it never names them explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The concrete example ('Mars Reconnaissance Orbiter HiRISE data collections targeting Mars') implies a usage scenario and shows how filters combine, but there is no explicit when-to-use/when-not guidance and no mention of the sibling search_* tools that cover adjacent entity types.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.