Itential MCP Server

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Python

Remote

Trigger Automation

trigger_automation

Destructive

Trigger any Itential workflow or agent automation by route name. Get a job or session object to monitor via describe_job or describe_session.

Instructions

Trigger an automation via its Operations Manager endpoint.

Executes any automation (workflow or agent) by calling its endpoint trigger. The response type depends on the automation's component type:

Workflow automations return a job object (StartWorkflowResponse) monitored via describe_job.
Agent automations return a session object (StartAgentResponse) monitored via describe_session.

Use get_automations to discover available automations and their component_type before triggering, so you know which monitoring tool to use afterward.

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": {
      "route_name": "<route_name>"
    },
    "name": "trigger_automation"
  }
}

Input Schema

Name	Required	Description	Default
`data`	No	Input data for the automation matching its endpoint trigger schema
`route_name`	Yes	The API route name of the automation to trigger (use route_name from get_workflows or get_automations)

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 4, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already mark readOnlyHint=false and destructiveHint=true, covering mutation safety. The description adds context that the response type (job vs session) depends on component_type and specifies which monitoring tool to use, which is useful beyond the annotations. No contradiction with annotations.

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 description is concise and well-structured: a single opening sentence, two bullet-like lines for response types, and a final discovery instruction. Every sentence serves a purpose and no unnecessary detail is included.

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?

Given the tool's complexity, the description covers the full workflow: discovering automations, triggering them, and monitoring the result via sibling tools. The output schema is present, and annotations cover side effects, making this description sufficiently complete for an agent to use the tool correctly.

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%, with both route_name and data already having descriptive text. The tool description only reiterates the route_name origin and does not add new semantic details about the parameters beyond the schema.

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 opens with 'Trigger an automation via its Operations Manager endpoint' and clearly states it executes any automation (workflow or agent), distinguishing it from sibling monitoring tools like describe_job and describe_session. It explicitly identifies the resource (automations) and the action (trigger).

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

Usage Guidelines4/5

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

It provides a clear usage pattern: use get_automations first to learn component_type, then trigger, then monitor via describe_job or describe_session depending on the type. However, it does not explicitly state when not to use this tool or how it compares to the sibling start_workflow tool.

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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