query_logs · Azure Log Analytics MCP Server MCP

WHAT IT DOES

What query_logs does on Azure Log Analytics MCP Server

AI agents invoke query_logs to trigger actions in Azure Log Analytics 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_logs needs a policy

Executing arbitrary KQL queries is an Execute-category action. While KQL is primarily a query language, running arbitrary code/queries against a live Azure Log Analytics workspace carries high blast radius: queries can exfiltrate sensitive log data, consume significant resources, and depending on workspace configuration may trigger downstream actions.

From the tool's definition 'Execute KQL query against Azure Log Analytics' — the tool runs arbitrary KQL queries against a live workspace. KQL supports data-modifying and potentially destructive operations depending on workspace permissions.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

query_logs Rate-limited

query_logs 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_logs": {
      "limits": [
        {
          "counter": "query_logs_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 Azure Log Analytics MCP Server, so you can run agents against it safely.

FAQ

Questions about query_logs

What does the query_logs tool do? +

Execute KQL query against Azure Log Analytics. It is categorised as a Execute tool in the Azure Log Analytics 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_logs? +

Register the Azure Log Analytics MCP Server MCP server in PolicyLayer and add a rule for query_logs: 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 Azure Log Analytics MCP Server. Nothing to install.

What risk level is query_logs? +

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

Can I rate-limit query_logs? +

Yes. Add a rate_limit block to the query_logs 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_logs completely? +

Set action: deny in the PolicyLayer policy for query_logs. 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_logs? +

query_logs is provided by the Azure Log Analytics MCP Server MCP server (rasta26/azure_log_mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.