Autonomous SRE & Distributed Incident Diagnosis MCP Server

simulate_incident_event

Inject synthetic distributed incidents, such as database pool exhaustion or 5xx spikes, into a target service to test incident detection, diagnosis, and remediation workflows.

Instructions

Inject a synthetic distributed incident (e.g. db connection pool exhaustion, 5xx spike, memory leak) for testing and evaluation.

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": {
      "serviceName": "<serviceName>",
      "incidentType": "<incidentType>"
    },
    "name": "simulate_incident_event"
  }
}

Input Schema

Name	Required	Description	Default
`severity`	No	Severity level of the injected failure (default "critical")	critical
`serviceName`	Yes	Service name to target (e.g. "order-service")
`incidentType`	Yes	Synthetic incident scenario to inject

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Nov 11, 2026

TDQS

B3.2/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The word 'synthetic' hints that this is a fabricated signal rather than a real outage, but it says nothing about blast radius — whether the injected event reaches real monitoring/alerting, how long it persists, whether it auto-expires, or how to remove it. For a state-mutating injection tool with zero annotation coverage, that is a significant gap.

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?

A single front-loaded sentence with the action first and the concrete scenarios in a parenthetical. No filler, no restatement of the name.

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

Completeness2/5

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

This is a moderately complex, state-changing tool with no annotations and no output schema. The description identifies what it does but omits what an agent most needs to call it responsibly: impact scope, duration, cleanup/rollback, and what the call returns.

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

Parameters3/5

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

Schema description coverage is 100%, and the enums for incidentType and severity are already documented in the schema. The examples in the description (pool exhaustion, 5xx spike, memory leak) loosely mirror the enum values but add no syntax or behavioral detail beyond them, so baseline 3 applies.

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 states a specific verb and resource ('Inject a synthetic distributed incident') and lists concrete example scenarios that map to the enum values. It is clearly distinct from the read-oriented siblings (query metrics, fetch traces, correlate with git), though it never explicitly names them.

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?

The trailing phrase 'for testing and evaluation' implies the intended context, which is enough to keep an agent from calling it in routine production diagnostics. However, there are no explicit exclusions, no prerequisites, and no advice on which sibling to use when the goal is actually to diagnose a real incident rather than fabricate one.

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

Deploy Server