Get REST API reference documentation for a specific Google Cloud service. WHEN TO USE: Use this tool when: - User needs API endpoints, methods, or parameters - User is developing integrations with GCP APIs - User asks about REST API for a specific GCP service - User needs to know available API re...
AI agents call get_api_reference to retrieve information from Google Cloud Docs MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool is purely informational, returning documentation and API reference materials for Google Cloud services. It supports natural language queries and content extraction but does not execute requests, modify data, delete resources, or trigger external operations.
From the tool's definition Tool retrieves and provides 'REST API reference documentation' with 'API endpoints, methods, or parameters' - all read-only operations. No modifications, deletions, code execution, or financial actions occur.
Attacks that exploit this kind of access
Get REST API reference documentation for a specific Google Cloud service. WHEN TO USE: Use this tool when: - User needs API endpoints, methods, or parameters - User is developing integrations with GCP APIs - User asks about REST API for a specific GCP service - User needs to know available API resources for a service INPUT: - service (required): GCP service name (compute, storage, bigquery, pubsub, sql, kubernetes, functions, run, iam) - resource (optional): Specific API resource (instances, buckets, datasets, topics, etc.) SUPPORTED SERVICES & RESOURCES: - compute: instances, disks, networks, firewalls, images, machineTypes - storage: buckets, objects, notifications - bigquery: datasets, tables, jobs, routines - pubsub: topics, subscriptions, snapshots - sql: instances, databases, users, backupRuns - kubernetes: clusters, nodePools, operations - functions: functions, operations, locations - run: services, configurations, routes, revisions - iam: roles, serviceAccounts, policies OUTPUT: Returns JSON with: - service: Service name - description: Service description - apiReferenceUrl: Full URL to API reference - availableResources: List of available resources for this service - documentation: Actual API documentation content (if available) EXAMPLE USAGE: - Get Compute Engine API overview: service=. It is categorised as a Read tool in the Google Cloud Docs MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Google Cloud Docs MCP Server MCP server in PolicyLayer and add a rule for get_api_reference: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Google Cloud Docs MCP Server. Nothing to install.
get_api_reference is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the get_api_reference rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for get_api_reference. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
get_api_reference is provided by the Google Cloud Docs MCP Server MCP server (longngo192/gcpdoc-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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