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google-cloud-console-mcp

google-cloud-console-mcp

by kutleloove
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

Get Firebase project

firebase_get_project

Fetch Firebase-specific metadata for a GCP project to inspect its Firebase configuration and status. Requires Firebase already enabled on the project.

Instructions

Fetches Firebase-specific metadata for a project (this requires Firebase to already be enabled on the GCP project — see firebase_add_firebase).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "firebase_get_project"
  }
}

Input Schema

NameRequiredDescriptionDefault
projectIdNoGCP/Firebase project id; defaults to GOOGLE_CLOUD_PROJECT env var

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
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 burden. It does usefully disclose the 'Firebase already enabled' precondition, but 'Fetches' only implies read-only and it says nothing about error behavior when Firebase is absent or what the response contains.

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, front-loaded sentence that states the operation first and the precondition second. Every clause earns its place with no filler.

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 one-parameter read tool with no output schema and no annotations, the description covers purpose and the important setup prerequisite. It is nearly complete, though it could have noted what metadata is returned or how it differs from the generic GCP getter.

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 the sole projectId parameter (including its GOOGLE_CLOUD_PROJECT default) is fully documented in structured data. The description adds no parameter-level detail beyond that, so the baseline of 3 applies.

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 ("Fetches") and resource ("Firebase-specific metadata for a project"), which cleanly separates it from the generic gcp_get_project sibling via the 'Firebase-specific' qualifier. It stops short of naming gcp_get_project explicitly, so an agent must infer the distinction rather than being routed directly.

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

Usage Guidelines3/5

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

Provides a real prerequisite — Firebase must already be enabled on the GCP project — and points the agent to firebase_add_firebase for that setup step. However, it never states when to prefer this over gcp_get_project or firebase_list_projects, leaving the core selection decision to inference.

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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