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GCP MCP

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Python
Hybrid

list_cloud_build_triggers

List Cloud Build triggers in a specified GCP project to manage and monitor automated build configurations efficiently.

Instructions

    List Cloud Build triggers in a GCP project.
    
    Args:
        project_id: The ID of the GCP project to list build triggers for
    
    Returns:
        List of Cloud Build triggers in the specified GCP project

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYes

Implementation Reference

  • src/gcp_mcp/gcp_modules/deployment/tools.py:38-50 (handler)
    The handler function implementing the 'list_cloud_build_triggers' tool logic (currently a TODO placeholder with input validation via type hints and docstring serving as schema). The @mcp.tool() decorator also handles registration.
    @mcp.tool()
def list_cloud_build_triggers(project_id: str) -> str:
    """
    List Cloud Build triggers in a GCP project.
    
    Args:
        project_id: The ID of the GCP project to list build triggers for
    
    Returns:
        List of Cloud Build triggers in the specified GCP project
    """
    # TODO: Implement this function
    return f"Not yet implemented: listing Cloud Build triggers for project {project_id}"
  • src/gcp_mcp/server.py:60-60 (registration)
    Top-level registration call for the deployment tools module, which registers the 'list_cloud_build_triggers' tool.
    deployment_tools.register_tools(mcp)
  • src/gcp_mcp/server.py:15-15 (registration)
    Import of the deployment tools module containing the 'list_cloud_build_triggers' implementation and registration.
    from .gcp_modules.deployment import tools as deployment_tools
  • src/gcp_mcp/gcp_modules/deployment/tools.py:6-7 (registration)
    The module-level register_tools function that defines and registers multiple tools, including 'list_cloud_build_triggers' via nested @mcp.tool() decorators.
    def register_tools(mcp):
    """Register all deployment tools with the MCP server."""

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.6/5.0
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It only states the operation and returns, without mentioning read-only behavior, side effects, pagination, or required permissions. The absence of such context is a significant gap.

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?

The description is compact and structured with a one-line purpose, Args, and Returns. Every sentence adds value, and the format is immediately scannable. No wasted words.

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?

For a simple one-parameter list operation, the description covers purpose, parameter, and return. However, it lacks explicit confirmation of read-only behavior or pagination details, which would make it more complete given the absence of annotations.

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?

The schema provides no description for the project_id parameter, but the docstring adds meaning: 'The ID of the GCP project to list build triggers for'. It also clarifies the return value. This compensates well for the schema's 0% coverage.

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 'List Cloud Build triggers in a GCP project' with a specific verb, resource, and scope. It distinguishes itself from sibling list tools (e.g., list_compute_instances, list_gke_clusters) by naming Cloud Build triggers 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?

No guidance is provided on when to use this tool versus alternatives. It does not mention exclusions, prerequisites, or alternative tools, leaving the agent to infer usage solely from the name and generic description.

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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