get_agent_runtime_endpoint
AI agents call get_agent_runtime_endpoint to retrieve information from Amazon Location Service MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The naming convention (get_*) and context within AWS Location Service suggest this retrieves runtime endpoint data without side effects. However, confidence is moderate due to empty description. Without additional details confirming destructive, execute, or write capabilities, classification defaults to Read with low severity as endpoint retrieval typically poses minimal risk in isolation.
From the tool's definition Tool name 'get_agent_runtime_endpoint' suggests retrieval of endpoint information. Description is empty, limiting certainty. The 'get_' prefix and absence of mutation/execution keywords indicate a read operation.
Documented attack patterns abuse exactly the kind of access get_agent_runtime_endpoint gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Amazon Location Service MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for get_agent_runtime_endpoint:
{
"version": "1",
"default": "deny",
"tools": {
"get_agent_runtime_endpoint": {}
}
} get_agent_runtime_endpoint is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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get_agent_runtime_endpoint. It is categorised as a Read tool in the Amazon Location Service MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Amazon Location Service MCP Server MCP server in PolicyLayer and add a rule for get_agent_runtime_endpoint: 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 Amazon Location Service MCP Server. Nothing to install.
get_agent_runtime_endpoint 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_agent_runtime_endpoint 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_agent_runtime_endpoint. 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_agent_runtime_endpoint is provided by the Amazon Location Service MCP Server MCP server (awslabs.aws-location-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Amazon Location Service MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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805 Amazon Location Service MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.