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Itential MCP Server

Itential MCP Server

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by itential
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Python
Remote

Start Workflow

start_workflow
Destructive

Triggers a workflow automation endpoint by route name. Provide route_name and optional data to execute the workflow.

Instructions

Triggers a workflow automation endpoint by route name.

This is a thin wrapper around trigger_automation, kept as a stable, workflow-specific entry point. trigger_automation is the general-purpose tool and also supports non-workflow automation types (e.g. agents).

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": "start_workflow"
  }
}

Input Schema

NameRequiredDescriptionDefault
dataNoData to include in the request body when calling the route
route_nameYesThe name of the API endpoint used to start the workflow

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false and destructiveHint=true, so the core behavioral profile is covered. The description adds only that it is a 'thin wrapper' and 'stable entry point,' which is contextual but not behavioral (e.g., no details on side effects, return behavior, or auth requirements).

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 two sentences, front-loaded with the primary purpose, then a concise note on the relationship to trigger_automation. Every sentence earns its place with zero redundancy.

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

Completeness4/5

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

For a simple wrapper with 2 parameters and a high-coverage schema, the description is complete enough. It names the sibling tool and clarifies the scope, while the existence of an output schema means return values don't need to be described. Minor gap: no mention of potential side effects beyond the annotation's destructiveHint, but that is already signal.

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%; both parameters are described in the schema. The description reinforces that the tool triggers 'by route name,' aligning with the route_name parameter, but adds no additional parameter-level detail beyond what the schema already provides.

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 a specific verb and resource: 'Triggers a workflow automation endpoint by route name.' It clearly distinguishes itself from trigger_automation by positioning itself as a workflow-specific wrapper, making its scope unambiguous.

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?

The description explicitly states when to use this tool versus the alternative: 'trigger_automation is the general-purpose tool and also supports non-workflow automation types (e.g. agents).' This gives clear guidance on when start_workflow is the appropriate choice.

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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