update_agent_runtime_endpoint
AI agents use update_agent_runtime_endpoint to create or update resources in Prometheus MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Prometheus MCP Server environment.
The name implies modifying an existing agent runtime endpoint, which is a Write operation. However, the description is empty, so confidence is reduced. Given the context of AWS Managed Prometheus and the potential impact of changing a runtime endpoint (could affect agent data ingestion pipelines), severity is rated high.
From the tool's definition Tool name 'update_agent_runtime_endpoint' — 'update' suggests a write/modify operation on an agent runtime endpoint configuration.
Documented attack patterns abuse exactly the kind of access update_agent_runtime_endpoint gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Prometheus MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for update_agent_runtime_endpoint:
{
"version": "1",
"default": "deny",
"tools": {
"update_agent_runtime_endpoint": {
"limits": [
{
"counter": "update_agent_runtime_endpoint_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
} update_agent_runtime_endpoint stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
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update_agent_runtime_endpoint. It is categorised as a Write tool in the Prometheus MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Prometheus MCP Server MCP server in PolicyLayer and add a rule for update_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 Prometheus MCP Server. Nothing to install.
update_agent_runtime_endpoint is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the update_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 update_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.
update_agent_runtime_endpoint is provided by the Prometheus MCP Server MCP server (awslabs.prometheus-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Prometheus 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 Prometheus MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.