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qgis-mcp

qgis-mcp

by Esaban17
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

inspect_dataset

Describe a vector or raster dataset to retrieve its CRS, extent, geometry, fields, and sample values.

Instructions

Describe a vector or raster file: CRS, extent, geometry, fields and sample values.

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": {
      "path": "<path>"
    },
    "name": "inspect_dataset"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It does disclose the returned content (CRS, extent, geometry, fields, sample values), which implies a read-only inspection, but it never confirms the operation is side-effect free, says nothing about supported formats, or how a missing/invalid path is handled.

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?

A single sentence with zero wasted words, front-loading the verb and resource and then listing the concrete outputs. Nothing is redundant or padded.

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 no output schema and no annotations, the description does well to enumerate the returned fields, which is the key return-value information. However, it omits error behavior, supported data formats, and any workflow context, leaving gaps for a tool that reads external files.

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 0% and the single `path` parameter has no description in the schema. The phrase "a vector or raster file" hints that `path` is a file path rather than a layer name and constrains the accepted inputs, but no format, relative-vs-absolute, or extension guidance is given.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a specific verb ("Describe") and resource ("a vector or raster file"), and it enumerates the exact outputs (CRS, extent, geometry, fields, sample values). It doesn't name or differentiate from siblings, but the sibling set (map/layer mutation and generation tools) is functionally distant, so disambiguation is barely needed.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use guidance, no mention of prerequisites (e.g. the file must exist on disk), and no explicit alternative tool. The implied workflow of inspecting a dataset before adding it as a layer is inferable from the sibling `add_layer`, but the description never states it.

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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