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cognigy-ai-mcp-management-server

cognigy-ai-mcp-management-server

by TsvetanG2
OverviewSchemaSourceRelated ServersDiscussions(1)Admin
TypeScript

clone_flow

Clone a Cognigy.AI flow to create an identical copy including all nodes, intents, and configurations within the same project.

Instructions

Clones a Cognigy.AI flow within the same project. Creates an exact copy of the flow including all nodes, intents, and configurations. The cloned flow gets an auto-generated name. MUTATING: Set dryRun=false to clone.

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": "clone_flow"
  }
}

Input Schema

NameRequiredDescriptionDefault
dryRunNoIf true (default), validates without cloning. Set to false to actually clone.
flowIdYesThe flow ID to clone

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.4

TDQS

A4.1/5.0
Behavior4/5

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

Annotations indicate readOnlyHint=false, and the description reinforces this with 'MUTATING.' It also clarifies the dryRun flag's role. No contradictions with annotations. Lacks disclosure of side effects or permissions, but adequate given 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 three sentences long, front-loaded with the action, and every sentence provides distinct information. No fluff, very efficient.

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

Completeness3/5

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

The description explains cloning and auto-naming but does not mention the output or return value (e.g., new flow ID). With no output schema, the agent is left to infer what happens after cloning. Could be more 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's 'Set dryRun=false to clone' adds value beyond the schema's parameter description. However, it does not elaborate on other parameters meaningfully, so 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 the action (clone), the resource (flow), and scope (within same project). It lists what is copied (nodes, intents, configurations) and mentions auto-generated name, distinguishing it from other flow operations.

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 'MUTATING: Set dryRun=false to clone,' guiding the agent on how to execute the mutation. It does not provide when-to-use vs alternatives, but the context is clear enough for the tool's purpose.

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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