qgis-dev-probe-mcp

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run_recipe

Runs a Python recipe from the configured recipe directory, passing optional arguments and a timeout to automate QGIS tasks.

Instructions

Run a recipe (a Python file with def run(ctx, args)) from the configured recipe directory.

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": {
      "name": "<name>"
    },
    "name": "run_recipe"
  }
}

Input Schema

Name	Required	Description	Default
`args`	No
`name`	Yes
`timeout_s`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 25, 2026

TDQS

C2.7/5.0

Behavior2/5

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

With no annotations at all, the description carries the full disclosure burden. It hints at arbitrary code execution by naming the Python entry point, but says nothing about side effects being permanent, permission/auth requirements, what happens on timeout, or what the call returns.

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?

A single front-loaded sentence with zero wasted words. It is efficiently written, but the brevity comes at the cost of leaving the operational detail absent rather than being an example of tight completeness.

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

Completeness2/5

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

For a tool that executes arbitrary Python with no annotations, no output schema, and 0% parameter documentation, this description is too thin. An agent cannot tell whether execution is sandboxed, how failures or timeouts surface, or how `args` is interpreted by the target recipe.

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

Parameters2/5

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

Schema description coverage is 0% for three parameters. The description implies `args` is forwarded to the recipe's `run(ctx, args)` call, which is genuinely useful, but `name` (must match a file in the recipe directory) and `timeout_s` (default 600, and the consequence of exceeding it) get no explanation anywhere.

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?

States a specific verb and resource ("Run a recipe") and defines what a recipe is ("a Python file with `def run(ctx, args)`") and where it lives (the configured recipe directory). That is enough to separate it from run_algorithm or trigger_action, though it never names a sibling explicitly.

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 guidance on when to pick this over execute_code or trigger_action, nor any note that a recipe name should first be discovered via list_recipes. The agent must infer usage entirely from the one-line purpose statement.

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