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mcp-gitlab-crunchtools

mcp-gitlab-crunchtools

by crunchtools
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Cancel Pipeline Tool

cancel_pipeline_tool

Cancels a running GitLab CI/CD pipeline using its project and pipeline ID to stop unwanted or stuck jobs.

Instructions

Cancel a running CI/CD pipeline.

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": {
      "project_id": "<project_id>",
      "pipeline_id": "<pipeline_id>"
    },
    "name": "cancel_pipeline_tool"
  }
}

Input Schema

NameRequiredDescriptionDefault
project_idYesProject ID or path
pipeline_idYesPipeline ID

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.6.0
    • addedInput schema / properties / pipeline_id / minimum
      Added value: +1
  2. First observedv0.4.1

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full behavioral burden, yet only implies a precondition ("running") without stating what happens if the pipeline is already finished, whether jobs are terminated, or whether the action is reversible. Permissions, side effects, and confirmation requirements are all unaddressed for a mutation operation.

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 filler, which is structurally clean. It is arguably over-terse for a destructive tool, but there is no wasted language to penalize.

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?

An output schema exists, so return values needn't be explained, which lowers the burden. Still, for an unannotated mutation tool the description lacks the precondition, side-effect, and sibling-differentiation details an agent needs to invoke it confidently.

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 100%, so project_id and pipeline_id are already fully documented in the schema, and the description adds nothing beyond them. Baseline 3 applies since the schema does all the work.

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?

"Cancel a running CI/CD pipeline" gives a specific verb (cancel) and resource (pipeline), so the core action is unambiguous. However, it does nothing to distinguish this from close siblings like delete_pipeline_tool, retry_pipeline_tool, or cancel_job_tool, leaving the agent to infer the boundary from names alone.

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?

The description offers no guidance on when to cancel versus delete or retry a pipeline, and no mention of prerequisites such as pipeline state. The agent must already know GitLab semantics to pick the right tool among the three pipeline-mutating 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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