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Metrx MCP Server

Metrx MCP Server

by metrxbots
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TypeScript
Remote

Get Policy Actuations

metrx_get_actuations
Read-onlyIdempotent

Retrieve org-scoped actuation records with action class, authority, who/when, rollback state, and acknowledgement status; configuration contents are excluded.

Instructions

Org-scoped actuation records: action class, authority, who/when, rollback state with reason, acknowledgement state. Config contents (from/to) are excluded. Requires the optimization_model_v3 flag (404 while off). Read-only. Response is envelope-shaped: every numeric leaf is a MeasuredValue {value, ci_low, ci_high, method, data_through}. ci fields are null unless the source payload carries a real confidence interval — never fabricated. Requires an API key with the 'read' scope.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "metrx_get_actuations"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.5.0

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover readOnly, idempotent and non-destructive, so the bar is lower, yet the description still adds real value: feature-flag gating with a 404 signal, the required auth scope, the exclusion of config contents, and the numeric-leaf contract where ci_low/ci_high are null rather than fabricated. It does not discuss pagination or result-size limits, which keeps it from a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The text is front-loaded with the returned resource and fields, then proceeds to exclusions, preconditions, and response shape. Every sentence conveys a distinct operational fact — flag gating, auth scope, CI null semantics — with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description carries the burden of describing the return shape and does so explicitly: envelope-shaped responses and a MeasuredValue leaf structure with honest CI semantics. Combined with auth, flag, and exclusion notes, an agent has everything needed to call and interpret this tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so there is nothing for the description to disambiguate; a 4 is the baseline for a parameterless tool. No misleading parameter language is present.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific resource (org-scoped actuation records) and enumerates the fields returned: action class, authority, who/when, rollback state with reason, acknowledgement state. It also states what is excluded (config from/to), which sharpens the boundary. It does not explicitly contrast with any sibling, so differentiation is left to the distinctive 'actuations' concept.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It supplies concrete preconditions — the optimization_model_v3 flag (404 while off) and an API key with 'read' scope — which tell the agent when the call will succeed. However, there is no explicit guidance on when to prefer this tool over alternatives, and no when-not guidance beyond the failure modes.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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