get_anomaly_explanation

SERVERDoit SOURCE@doitintl/doit-mcp-server

Low RISK CLASS

Category Read

Parameters 21 required

Recommended Allowedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/doit/get-anomaly-explanation.md

WHAT IT DOES

What get_anomaly_explanation does on Doit

AI agents call get_anomaly_explanation to retrieve information from Doit without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

Parameter	Type	Required	Description
`id`	string	Yes
`customerContext`	string	—	Scope the request to a specific customer by ID. Required for DoiT employees (whose token isn't tied to a single customer); omit for direct customer users.

Parameters from the server's own tool schema.

RISK

Why get_anomaly_explanation is rated Low

Even though get_anomaly_explanation only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs get_anomaly_explanation safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Doit, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For get_anomaly_explanation, this is the rule to start with:

get_anomaly_explanation Allowed

get_anomaly_explanation is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "get_anomaly_explanation": {}
  }
}

ALLOW ONLY THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Doit, apply this rule, and every get_anomaly_explanation call is checked against it from then on.

FAQ

Questions about get_anomaly_explanation

What does the get_anomaly_explanation tool do? +

Monitor cost spikes in your cloud environment. Returns a likely-cause explanation for the specified anomaly, alongside the deterministic facts and evidence references it was generated from. The explanation itself is AI-generated; it is always returned separately from the deterministic facts, and is marked as such in the explanation object. Generation is ephemeral: no conversation is persisted on your behalf. It is categorised as a Read tool in the Doit MCP Server, which means it retrieves data without modifying state.

What parameters does get_anomaly_explanation accept? +

get_anomaly_explanation accepts 2 parameters: id, customerContext. Required: id. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on get_anomaly_explanation? +

Register the Doit MCP server in PolicyLayer and add a rule for get_anomaly_explanation: 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 Doit. Nothing to install.

What risk level is get_anomaly_explanation? +

get_anomaly_explanation is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit get_anomaly_explanation? +

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

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

get_anomaly_explanation is provided by the Doit MCP server (@doitintl/doit-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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