Helps design microservice architectures for specific domains. Provides service boundary recommendations and communication patterns. Includes deployment and orchestration considerations. Uses the configured Vertex AI model (${modelIdPlaceholder}) with Google Search. Requires
AI agents call microservice_design_assistant to retrieve information from Vertex AI MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This is a consultation/recommendation tool that reads data and documentation to inform architectural decisions. It does not create infrastructure, execute deployments, modify systems, or commit financial resources. The tool gathers and synthesizes information (Read category behavior) without causing side effects or state changes to external systems.
From the tool's definition Tool 'microservice_design_assistant' provides recommendations and analysis ('Helps design', 'Provides service boundary recommendations', 'communication patterns', 'deployment and orchestration considerations').
Documented attack patterns abuse exactly the kind of access microservice_design_assistant gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Vertex AI MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for microservice_design_assistant:
{
"version": "1",
"default": "deny",
"tools": {
"microservice_design_assistant": {}
}
}microservice_design_assistant is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
Free to start. No card required.
Helps design microservice architectures for specific domains. Provides service boundary recommendations and communication patterns. Includes deployment and orchestration considerations. Uses the configured Vertex AI model (${modelIdPlaceholder}) with Google Search. Requires. It is categorised as a Read tool in the Vertex AI MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Vertex AI MCP Server MCP server in PolicyLayer and add a rule for microservice_design_assistant: 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 Vertex AI MCP Server. Nothing to install.
microservice_design_assistant 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 microservice_design_assistant 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 microservice_design_assistant. 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.
microservice_design_assistant is provided by the Vertex AI MCP Server MCP server (shariqriazz/vertex-ai-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 20 Vertex AI MCP Server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
20 Vertex AI MCP Server tools catalogued and risk-classified — across an index of 42,500+ MCP servers.