Skip to main content
Glama

DaedalMap World Development Indicators

Query Dataset

query_dataset
Read-only

Generic structured query for direct source_id or pack_id access using the same contract as POST /api/v1/query/dataset. Free packs: currency, distributed_manufacturing, floods, nri, owid, un_sdg, un_wpp, volcanoes, world_bank_wdi. Paid packs: earthquakes, hurricanes, tornadoes, tsunamis, wildfires, world_factbook, worldpop (x402 Base USDC).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoOptional sort instructions for row-returning queries.
limitNoMaximum number of rows to return for the requested source or pack.
outputNoOptional output controls such as response format hints.
filtersNoStructured filters including time, region_ids, and compare clauses.
metricsNoMetric ids to return. Use event_count for aggregate counts when supported.
pack_idNoPack identifier from get_catalog. Newly catalog-admitted packs require no MCP schema change.
source_idNoConcrete source id such as 'earthquakes_events', 'volcanoes_events', 'hurricanes_events', or 'un_sdg/01'.
request_idNoOptional caller-supplied request id for tracing and idempotency.

TDQS

A3.7/5.0
Behavior3/5

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

Annotations declare readOnlyHint=true, so safety is covered. The description adds context like the pack list and the API contract reference, but does not describe response format, pagination behavior, or any rate limits. With annotations bearing the safety burden, this is adequate but not rich.

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

Conciseness5/5

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

The description is two sentences: the first front-loads the core purpose and contract, the second provides actionable context (pack lists and pricing). There is no filler; every clause serves a purpose.

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?

With 8 optional parameters, nested objects, no output schema, and only readOnlyHint as annotation, the description gives a reasonable entry point by referencing the API contract and pack list. However, it omits details on response format, error handling, or how filters/metrics interplay, which an agent might need for confident invocation. It is adequate but not thorough.

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%, so the schema already documents each parameter. The description adds value beyond the schema by providing concrete examples like 'earthquakes_events' and mentioning 'Use event_count for aggregate counts when supported', which clarifies intended usage for metrics. However, it does not systematically elaborate on each parameter beyond the 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?

The description states a specific verb (query) and resource (dataset) with clear scope: direct source_id or pack_id access. It also references the API contract and lists free and paid packs, which helps distinguish it from siblings like get_pack or get_catalog, which likely provide metadata rather than data queries.

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 phrase 'for direct source_id or pack_id access' implies usage when the caller already knows the ID, and the listing of packs suggests when it's applicable. However, it does not explicitly state when to use alternatives (e.g., get_catalog for listing, get_pack for pack metadata) or when not to use this tool, leaving the routing partly implicit.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.2/5.0
Disambiguation5/5

Each tool has a clearly distinct role: get_catalog lists available packs, get_pack provides detailed metadata for one pack, get_tool_help offers guidance on other tools, and query_dataset executes data queries. No overlap or ambiguity between them.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern (get_catalog, get_pack, get_tool_help, query_dataset) with snake_case and a clear verb prefix. This is predictable and uniform.

Tool Count5/5

Four tools is a well-scoped set for a data access server: two for discovery (catalog and pack metadata), one for meta-guidance, and one for querying. This is within the ideal 3-15 range and each tool earns its place.

Completeness5/5

The surface covers the full lifecycle of a data access workflow: discover (get_catalog), understand (get_pack), learn to use (get_tool_help), and query (query_dataset). There are no obvious missing operations for a read-only data server.