query_prometheus | PolicyLayer

WHAT IT DOES

What query_prometheus does on Kubernetes + Prometheus SRE MCP Server

AI agents invoke query_prometheus to trigger actions in Kubernetes + Prometheus SRE MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.

WHY IT NEEDS A POLICY

Why query_prometheus needs a policy

This tool executes arbitrary PromQL queries against a Prometheus instance. While PromQL is primarily a read/query language, it runs against a live external system and could be used to execute complex or resource-intensive queries (e.g., high-cardinality queries causing performance issues). The 'Run' framing and arbitrary query execution place it in Execute rather than Read.

From the tool's definition "Run a PromQL query against Prometheus" — the word 'Run' indicates execution of an arbitrary query against an external system.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

query_prometheus Rate-limited

query_prometheus stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "query_prometheus": {
      "limits": [
        {
          "counter": "query_prometheus_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Kubernetes + Prometheus SRE MCP Server, so you can run agents against it safely.

FAQ

Questions about query_prometheus

What does the query_prometheus tool do? +

Run a PromQL query against Prometheus. It is categorised as a Execute tool in the Kubernetes + Prometheus SRE MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on query_prometheus? +

Register the Kubernetes + Prometheus SRE MCP Server MCP server in PolicyLayer and add a rule for query_prometheus: 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 Kubernetes + Prometheus SRE MCP Server. Nothing to install.

What risk level is query_prometheus? +

query_prometheus is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit query_prometheus? +

Yes. Add a rate_limit block to the query_prometheus 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.

How do I block query_prometheus completely? +

Set action: deny in the PolicyLayer policy for query_prometheus. 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.

What MCP server provides query_prometheus? +

query_prometheus is provided by the Kubernetes + Prometheus SRE MCP Server MCP server (manishmaurya22/sre-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.