save_query · Azure Log Analytics MCP Server MCP

WHAT IT DOES

What save_query does on Azure Log Analytics MCP Server

AI agents use save_query to create or update resources in Azure Log Analytics MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Azure Log Analytics MCP Server environment.

WHY IT NEEDS A POLICY

Why save_query needs a policy

The tool creates or modifies saved query artifacts within the Azure Log Analytics workspace. While reversible and non-destructive, it constitutes a Write operation as it persists new configuration state.

From the tool's definition Tool name 'save_query' and description 'Save KQL query for reuse' indicate creation/storage of query definitions in Azure Log Analytics workspace. This is a reversible write operation that stores metadata (saved queries) without modifying underlying data.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

save_query Rate-limited

save_query 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "save_query": {
      "limits": [
        {
          "counter": "save_query_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

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 save_query

What does the save_query tool do? +

Save KQL query for reuse. It is categorised as a Write tool in the Azure Log Analytics MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on save_query? +

Register the Azure Log Analytics MCP Server MCP server in PolicyLayer and add a rule for save_query: 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 save_query? +

save_query is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit save_query? +

Yes. Add a rate_limit block to the save_query 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 save_query completely? +

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

save_query 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.