cognigy-ai-mcp-management-server

create_package

Create a package bundling flows, endpoints, and other resources from a Cognigy.AI project for transfer between projects. Set dryRun=false to execute.

Instructions

Creates a package from selected resources in a Cognigy.AI project. Packages bundle flows, endpoints, and other resources for transfer between projects. MUTATING: Set dryRun=false to create. Async operation.

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": {
      "projectId": "<projectId>",
      "name": "<name>",
      "resourceIds": "<resourceIds>"
    },
    "name": "create_package"
  }
}

Input Schema

Name	Required	Description
`name`	Yes	Name for the package
`dryRun`	No	If true (default), validates without creating. Set to false to actually create.
`projectId`	Yes	The project ID to create the package in
`timeoutMs`	No	Maximum time to wait for package creation (5-600 seconds, default 120)
`description`	No	Optional description of the package
`resourceIds`	Yes	Array of resource IDs to include in the package (flows, endpoints, etc.)
`pollIntervalMs`	No	How often to check task status (1-10 seconds, default 3)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.4Jul 27, 2026

TDQS

A4.4/5.0

Behavior5/5

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

The description adds significant behavioral context beyond annotations: it explicitly states 'MUTATING', 'Set dryRun=false to create', and 'Async operation'. Annotations only indicate readOnlyHint=false, idempotentHint=false, and destructiveHint=false, so the description enriches the agent's understanding without contradiction.

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 extremely concise (two sentences plus a short note) and front-loaded with the core action. Every sentence adds value without 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?

Given the tool's complexity (7 parameters, 3 required, async) and no output schema, the description covers the creation action, async behavior, and dryRun mode. However, it omits details about the return value (likely a task), which would improve completeness.

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%, so baseline is 3. The description reiterates the dryRun parameter's role but doesn't add meaning beyond the schema. No other parameters are elaborated, making the description's contribution minimal.

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 ('creates a package') and the resource ('package from selected resources in a Cognigy.AI project'). It also explains the bundling purpose, distinguishing it from sibling tools like list_packages or delete_package.

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 provides explicit guidance: it is mutating, dryRun=false is required for actual creation, and the operation is async. This helps the agent understand when to use this tool, though it doesn't list alternatives or when not to use it.

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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