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QGIS MCP

QGIS MCP

by lefcgis
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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Validate Expression

validate_expression
Read-only

Check if a QGIS expression is valid. Returns parse errors and referenced column names, with optional validation against a layer's fields.

Instructions

Validate a QGIS expression. Returns whether it's valid, any parse errors, and referenced column names. Optionally test against a layer's fields.

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": {
      "expression": "<expression>"
    },
    "name": "validate_expression"
  }
}

Input Schema

NameRequiredDescriptionDefault
layer_idNo
expressionYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the description adds value by detailing what the tool returns (validity, errors, column names) and the optional layer context, without contradicting annotations.

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 concise sentences, front-loaded with the core purpose, and every word adds value. No extraneous information.

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 the tool's complexity (two parameters, no nested objects) and the presence of an output schema, the description sufficiently covers its functionality. Minor gap: no mention of output format, but output schema likely covers that.

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?

With 0% schema description coverage, the description compensates by explaining that 'expression' is validated and 'layer_id' optionally tests against layer fields. This adds meaningful context beyond parameter names.

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 it validates a QGIS expression and returns specific outputs (validity, parse errors, referenced column names). It also mentions optional testing against a layer's fields, fully distinguishing its purpose from siblings like evaluate_expression.

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 description implies usage for validating expressions but does not explicitly state when to use it versus alternatives (e.g., evaluate_expression). No when-not or exclusions are provided.

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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