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geolens-mcp

geolens-mcp

Official
by geolens-io
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

search_datasets

Search the GeoLens catalog by free text to find datasets. Returns compact records with IDs, bounding boxes, and metadata for use in other catalog tools.

Instructions

Search the GeoLens catalog for datasets by free text.

Matches title, description, and keywords (semantic ranking is used automatically when the instance has it enabled). Returns a compact FeatureCollection (numberMatched, numberReturned, features) where each feature is a trimmed dataset record: id, bbox, and properties title, description (cut at 300 characters), record_type, geometry_type, feature_count, crs, keywords and updated. Use the feature id as the dataset_id for the other tools; get_dataset_schema has the full detail. Each feature's properties also include source_origin (upload, postgis, service, stac, created, or null) and source_freshness (fresh, due, overdue, or unknown). Freshness is advisory: due means one declared update interval has elapsed, while overdue means two have elapsed; neither proves that the content is wrong.

Search does not make a detail request per result. When the catalog summary has no health/check/refresh value, source_health, source_health_detail, last_checked_at, and last_refreshed_at are null. Call get_dataset_schema for populated trust metadata. Raw provider URLs and credentials are never included in these source-state fields.

Args: query: Search text. limit: Max results (1-200, default 10). offset: Result offset for paging.

Input Schema

NameRequiredDescriptionDefault
limitNo
queryYes
offsetNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv1.25.1
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / limit / maximum
      Added value: +200
    • addedInput schema / properties / limit / minimum
      Added value: +1
    • addedInput schema / properties / offset / minimum
      Added value: +0
  2. First observedv0.1.0

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so well: it discloses semantic ranking, that no per-result detail request is made, that descriptions are truncated at 300 characters, the exact meaning of `due` vs `overdue` freshness (explicitly advisory, not proof of wrongness), null-field conditions for health metadata, and that raw provider URLs and credentials are never returned.

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?

Purpose and return shape are front-loaded, and most sentences carry real information. The source-health paragraph is slightly bloated and discusses `source_health`, `last_checked_at`, and `last_refreshed_at` fields that are not even in the enumerated property list, which adds length without a clear payoff for a search call.

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

Completeness5/5

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

There is no output schema, so the description must define the return shape, and it does: a compact FeatureCollection with `numberMatched`, `numberReturned`, and a full enumeration of each feature's properties. An agent has everything needed to call this and interpret the response without a follow-up tool call.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate, and its Args block covers all three parameters: query as search text, limit as max results with the 1-200 range and default, and offset as the paging cursor. The coverage is adequate but terse; it does not clarify tokenization, empty-query behavior, or how offset interacts with ranked results.

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?

States a specific verb and resource ("Search the GeoLens catalog for datasets by free text") and immediately scopes what fields are matched. It also routes the agent onward ("Use the feature `id` as the dataset_id for the other tools; `get_dataset_schema` has the full detail"), which distinguishes it from the sibling that returns full detail.

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?

Clear context for when to use it (free-text discovery over the catalog) plus explicit hand-off guidance to `get_dataset_schema` for detail and trust metadata. It stops short of naming when *not* to use it versus siblings like `query`, `list_maps`, or `get_features`, so it is strong but not exhaustive.

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

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