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cognigy-ai-mcp-management-server

cognigy-ai-mcp-management-server

by TsvetanG2
OverviewSchemaSourceRelated ServersDiscussions(1)Admin
TypeScript

get_flow

Read-onlyIdempotent

Retrieve detailed metadata about a Cognigy.AI flow to inspect its configuration, locale info, and timestamps before modification.

Instructions

Gets detailed metadata about a specific Cognigy.AI flow. Returns flow configuration, locale info, and timestamps. Use this to inspect a flow before modifying it.

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": {
      "flowId": "<flowId>"
    },
    "name": "get_flow"
  }
}

Input Schema

NameRequiredDescriptionDefault
flowIdYesThe flow ID to retrieve

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.4

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds value by specifying the return content (configuration, locale info, timestamps), which is behavioral context beyond the 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?

Two sentences, no fluff, front-loaded with purpose and return details. Every sentence is useful.

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?

For a simple retrieval tool with one parameter, good annotations, and no output schema, the description adequately covers the return values and usage intent. It is complete.

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 coverage is 100% and the description does not add any parameter-specific information beyond what the schema already provides (flowId). Baseline 3 is appropriate.

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 gets detailed metadata about a specific flow, listing specific return fields (configuration, locale, timestamps). This distinguishes it from sibling tools like get_flow_settings or get_node.

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?

The description explicitly says 'Use this to inspect a flow before modifying it,' providing clear usage context. It does not mention when not to use it or alternatives, but the guidance is strong.

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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