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Metrx MCP Server

Metrx MCP Server

by metrxbots
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

Get Failure Predictions

metrx_get_failure_predictions
Read-onlyIdempotent

Forecast error-rate breaches, latency degradation, cost overruns and traffic anomalies for one agent using its last 7 days of calls against a 30-day baseline, with severity and recommended actions.

Instructions

Predictive failure analysis for ONE agent, computed on request from its last 7 days of calls against a 30-day baseline: error-rate breaches, latency degradation, cost overruns and traffic anomalies, each with severity, confidence, trend and recommended actions. Needs at least 20 calls in the last 7 days — below that it returns no predictions, which means too little data, not a healthy agent. Do NOT use for current/past failures — use get_alerts for active issues. Requires an API key with the 'read' scope.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "agent_id": "<agent_id>"
    },
    "name": "metrx_get_failure_predictions"
  }
}

Input Schema

NameRequiredDescriptionDefault
agent_idYesAgent (UUID) to analyze
severityNoOnly show predictions of this severity

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv0.5.0
    • changedInput schema / properties / agent_id / description
      Previous value: -"Filter predictions for a specific agent"New value: +"Agent (UUID) to analyze"
    • changedInput schema / properties / severity / description
      Previous value: -"Filter by prediction severity"New value: +"Only show predictions of this severity"
    • removedInput schema / properties / status
      Removed value: -{
-  "default": "active",
-  "description": "Filter by prediction status (default: active)",
-  "enum": [
-    "active",
-    "acknowledged",
-    "resolved"
-  ],
-  "type": "string"
-}
    • addedInput schema / required
      Added value: +[
+  "agent_id"
+]
  2. First observedv0.1.2

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the read-only/idempotent annotations, it discloses that results are computed on request against a 30-day baseline, and critically that an empty result signals insufficient data rather than a healthy agent — a semantic trap the annotations could never convey. It also states the 'read' API scope requirement.

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 capability statement, output payload, data threshold, and sibling exclusion are packed into four dense sentences with no filler. The most decision-relevant content (single-agent scope, get_alerts exclusion) is front-loaded.

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?

With no output schema, the description compensates by naming the per-prediction fields (severity, confidence, trend, recommended actions). Combined with the data threshold, empty-result semantics, and auth scope, nothing an agent needs to call this correctly is missing.

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?

Schema coverage is 100%, so the baseline is 3, and the description goes slightly beyond by emphasizing single-agent scoping ('ONE agent') and the 20-call data floor that governs whether agent_id will return anything. It does not mention the optional severity filter, leaving that entirely to the schema's enum.

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

Purpose5/5

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

The description gives a specific verb and resource ('Predictive failure analysis') scoped to 'ONE agent' and enumerates the four signal classes it covers (error-rate breaches, latency degradation, cost overruns, traffic anomalies). It explicitly distinguishes itself from the sibling get_alerts, so an agent can route without opening either schema.

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

Usage Guidelines5/5

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

It names the exact exclusion — 'Do NOT use for current/past failures — use get_alerts for active issues' — and states the data precondition (at least 20 calls in 7 days) that determines whether the tool is meaningful. Both the when-to-use and when-not-to-use conditions are explicit.

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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