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QGIS MCP

QGIS MCP

by lefcgis
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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Identify Features

identify_features
Read-only

Identify features at a given point coordinate across multiple vector layers, with optional tolerance for nearby searches and a limit on results per layer.

Instructions

Identify features at a point [x, y] in project CRS across layers (map-click analogue). tolerance (map units) expands the search; 0 = exact hit. layer_ids limits the search (default: visible vector layers). limit caps features per layer.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "point": "<point>"
    },
    "name": "identify_features"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
pointYes
layer_idsNo
toleranceNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.0

TDQS

A4.5/5.0
Behavior4/5

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

The description adds context beyond the readOnlyHint annotation by detailing search behavior (point, tolerance, layer filtering), defaults, and the 'map-click analogue' semantics.

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?

Two sentences, each adding essential information: first defines purpose and point, second details remaining parameters. No fluff, every part earns its place.

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?

For a read-only tool with 4 parameters and no output schema, the description covers inputs well. Lacks mention of return format (e.g., feature IDs, attributes), but is sufficient for basic use.

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 has 0% description coverage, but the description fully explains each parameter: point, tolerance (with units), layer_ids (default visible vector layers), and limit. This compensates entirely for missing schema descriptions.

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 clearly states the tool identifies features at a point, using specific verb-resource. It likens it to a map-click analogue, distinguishing it from selection tools like 'select_features'.

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?

The description explains parameters like tolerance, layer_ids, and limit, indicating when to adjust search radius, scope layers, and cap results. However, it does not explicitly state when not to use this tool versus siblings.

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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