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ServiceNow CMDB MCP Server

by ketiil

get_flows

Read-onlyIdempotent

Get Flow Designer flows related to a CMDB table or matching a name. Supports filtering by active status and pagination.

Instructions

Get Flow Designer flows related to a CMDB table or matching a name.

Searches sys_hub_flow by internal_name (CONTAINS table) and/or display name (CONTAINS name_filter). At least one of table or name_filter must be provided. Note: flow trigger/action details are stored in sub-tables, so this provides an overview — use the ServiceNow UI for full flow logic.

Examples: get_flows(table="cmdb_ci_server") get_flows(name_filter="decommission") get_flows(name_filter="Payroll", active_only=False)

Args: table: Filter flows whose internal_name contains this value (e.g. cmdb_ci_server). Optional if name_filter is provided. name_filter: Filter flows whose display name contains this value (e.g. "decommission", "Payroll"). Optional if table is provided. active_only: If True, return only active flows. Defaults to True. limit: Maximum flows to return (1-1000, default 25). offset: Pagination offset.

Returns: JSON object with "count", "total_count", "has_more", "next_offset", "suggested_next", and "flows" list containing sys_id, name, internal_name, description, active, and run_as. Also echoes "table" and/or "name_filter" when those parameters were provided.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableNo
name_filterNo
active_onlyNo
limitNo
offsetNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Annotations declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. Description adds context: searches sys_hub_flow, notes trigger/action details are in sub-tables (limitation), and lists return fields. No contradiction.

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

Conciseness4/5

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

Well-structured with examples, args list, and clear sections. Slightly verbose but every sentence adds value. Front-loaded with main action.

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 5 parameters, annotations, and output schema, the description covers input, output, limitations, and usage. Output schema exists, so return format is not needed in description. Complete for the tool complexity.

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

Parameters5/5

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

Schema coverage is 0%, but description fully explains each parameter with defaults, examples, and constraints. Also details return JSON structure, adding value 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 clearly states it retrieves Flow Designer flows by internal_name or display name, with specific criteria. It distinguishes from siblings like 'get_flow_details' by noting it provides an overview.

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?

Explicitly requires at least one of table or name_filter. Provides examples. Implicitly contrasts with 'get_flow_details' and ServiceNow UI, but does not explicitly list when-not-to-use.

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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