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geolens-mcp

geolens-mcp

Official

get_map

Retrieve a saved map’s summary, including name, visibility, view state, basemap, terrain, and layer list, to review its configuration without styling or sample values.

Instructions

Get a summary of one saved map: name, description, visibility, view state (center, zoom, bearing, pitch), basemap, terrain configuration and layer list.

Each layer has id, dataset_id, dataset_name, dataset_table_name, dataset_geometry_type, display_name, visible, layer_type and filter. Styling, popups, labels, column info and sample values are not included. dashboard_widget_count is the number of dashboard widgets (0 for none).

Args: map_id: Map id (e.g. from list_maps).

Input Schema

NameRequiredDescriptionDefault
map_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.25.1
    • addedInput schema / additionalProperties
      Added value: +false
  2. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the burden, and it does well by disclosing what is deliberately excluded (styling, popups, labels, column info, sample values) so the agent won't expect those fields. It also defines the semantics of dashboard_widget_count ('0 for none'). Missing only auth/permission and pagination context, which is minor for a single-record read.

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?

Front-loaded with the core purpose, followed by a compact field inventory and an explicit exclusion list. The layer-field catalog is a bit list-heavy but every item earns its place as return-shape documentation; no filler sentences.

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 describing return values is the description's job, and it does so thoroughly at both the top level and per-layer, plus calls out absent data. An agent can decide to call this and interpret the result without further sources.

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?

The single parameter has 0% schema description coverage, so the description must compensate: it documents map_id as a 'Map id' with provenance ('from list_maps'), which is meaningfully more than the bare type in the schema. It doesn't specify the ID format or null/failure behavior, keeping it from a 5.

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 ('Get a summary of one saved map') and enumerates exactly what the summary contains (name, description, visibility, view state, basemap, terrain, layers). This clearly distinguishes it from list_maps, which is named as the source of map_id, and from dataset-oriented siblings.

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 clear workflow context by telling the agent where map_id comes from ('e.g. from list_maps'), which implicitly scopes this tool to retrieving a single already-known map. It does not explicitly state when not to use it or contrast with get_dataset_schema, so it stops short of full when/when-not guidance.

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