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AQUAVIEW MCP

by org.aquaview.mcp

get_item

Fetch a single AQUAVIEW dataset item with full details, properties, and download links (assets).

STAC items embed assets inline — each asset includes an href (download URL) and media type, so there is no need for a separate "files" call.

Args: collection: The collection ID the item belongs to (e.g., "NOAA", "NDBC", "WOD"). Available from search results or list_collections. item_id: The unique item identifier (e.g., "wod_xbt_ZZ144579"). Available from search results. output_format: "toon" (default) or "json".

Returns: Full STAC item with geometry, properties (title, description, datetime, institution, variables, etc.), and assets (download links with media types).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
item_idYes
collectionYes
output_formatNotoon

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed4 schema fields changed
    • removedInput schema / additionalProperties
      Removed value: -false
    • removedInput schema / properties / collection / description
      Removed value: -"The collection ID the item belongs to (e.g., \"NOAA\", \"NDBC\", \"WOD\"). Available from search results or list_collections."
    • removedInput schema / properties / item_id / description
      Removed value: -"The unique item identifier (e.g., \"wod_xbt_ZZ144579\"). Available from search results."
    • removedInput schema / properties / output_format / description
      Removed value: -"\"toon\" (default) or \"json\"."
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

No annotations provided, so description carries burden. It discloses return structure (STAC item with geometry, properties, assets) and output_format default. Does not mention auth or destructive behavior, but fetch implies read-only.

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?

Well-structured with Args and Returns sections. Sentences are informative, though the line about STAC embedding assets could be considered slightly extra but adds value. Overall efficient.

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

Completeness4/5

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

Given 3 params, 0% coverage, no annotations, but has output schema, description is complete. Explains all params and return schema. Could mention error handling but not critical.

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

Parameters5/5

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

Schema coverage is 0%, but description thoroughly explains each parameter: collection (with examples), item_id (with examples), output_format (enum values and default). Adds significant meaning beyond schema.

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

Purpose5/5

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

Description clearly states 'Fetch a single AQUAVIEW dataset item with full details, properties, and download links.' This distinguishes it from siblings like list_collections and search_datasets.

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

Usage Guidelines4/5

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

Provides guidance on obtaining collection and item_id from search results or list_collections, and explains no need for separate files call. However, lacks explicit when-not-to-use or alternatives beyond implied context.

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

All AQUAVIEW MCP toolsInspect
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TDQS

A4.7/5.0
Disambiguation5/5

Each tool targets a distinct operation: listing collections, searching datasets, fetching item details, and running aggregations. No functional overlap.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern: list_collections, search_datasets, get_item, aggregate.

Tool Count5/5

Four tools cover the core operations of a catalog server without being excessive or insufficient. The scope is well-defined.

Completeness5/5

The tool set provides a complete read-only interface: list collections, search with filters, retrieve items with assets, and aggregate statistics. No obvious gaps.

Resources