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QGIS MCP

QGIS MCP

by lefcgis
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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Add Table Join

add_table_join

Add a table join to a vector layer, linking attributes from another layer via matching fields.

Instructions

Add a table join to a vector 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": {
      "target_layer_id": "<target_layer_id>",
      "join_layer_id": "<join_layer_id>",
      "target_field": "<target_field>",
      "join_field": "<join_field>"
    },
    "name": "add_table_join"
  }
}

Input Schema

NameRequiredDescriptionDefault
prefixNo
join_fieldYes
target_fieldYes
join_layer_idYes
target_layer_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.0

TDQS

C2.4/5.0
Behavior2/5

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

The description lacks behavioral details. It implies a mutation (adding a join) but does not explain whether it modifies the layer permanently, if it can be undone, or any side effects. With no annotations, the burden on the description is high, and it fails to provide sufficient transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with no fluff, achieving conciseness. However, it is overly sparse and under-specifies the tool's functionality, which detracts from its effectiveness.

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

Completeness1/5

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

Given the tool has 5 parameters and no output schema, the description is far from complete. It does not explain the join operation, required configurations, or expected outcomes, leaving an agent with insufficient information.

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

Parameters1/5

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

Schema description coverage is 0%, meaning the input schema provides no descriptions for parameters. The description does not explain any parameter meanings (e.g., prefix, target_layer_id, join_field). This is a critical gap for a tool with 5 parameters.

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 clearly states the action: add a table join to a vector layer. It uses a specific verb and mentions the resource. However, it does not differentiate from the sibling tool 'spatial_join', which serves a similar purpose.

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?

No guidance is provided on when to use this tool versus alternatives like spatial_join or add_features. There is no mention of prerequisites, limitations, or recommended contexts.

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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