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cognigy-ai-mcp-management-server

cognigy-ai-mcp-management-server

by TsvetanG2
OverviewSchemaSourceRelated ServersDiscussions(1)Admin
TypeScript

create_function

Creates a new Cognigy.AI function for custom code modules used in integrations, scheduled jobs, or computations. Set dryRun=false to create; default validates only.

Instructions

Creates a new Cognigy.AI Function. Functions are custom code modules for integrations, scheduled jobs, or computations. MUTATING: Set dryRun=false to create.

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>"
    },
    "name": "create_function"
  }
}

Input Schema

NameRequiredDescriptionDefault
codeNoThe function code (JavaScript/TypeScript). Runtime input arrives via trigger_function's parameters.
nameYesName for the function
dryRunNoIf true (default), validates without creating. Set to false to actually create.
projectIdYesThe project ID to create the function in

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv0.2.1
    • changedInput schema / properties / code / description
      Previous value: -"The function code (JavaScript/TypeScript)"New value: +"The function code (JavaScript/TypeScript). Runtime input arrives via trigger_function's parameters."
    • removedInput schema / properties / description
      Removed value: -{
-  "description": "Description of the function's purpose",
-  "type": "string"
-}
    • removedInput schema / properties / parameters
      Removed value: -{
-  "additionalProperties": {},
-  "description": "Function parameters schema",
-  "propertyNames": {
-    "type": "string"
-  },
-  "type": "object"
-}
    • removedInput schema / properties / type
      Removed value: -{
-  "description": "Function type",
-  "type": "string"
-}
  2. First observedv0.1.4

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already cover the mutation/safety profile (readOnlyHint=false, destructiveHint=false, openWorldHint=true), so the bar is lower. The description adds real value beyond them: it discloses the dry-run-by-default behavior ('validates without creating') and explains that function code receives runtime input via trigger_function's parameters. It does not describe what the create response returns.

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?

Three short sentences, front-loaded with the action, then the concept definition, then the critical execution caveat. No filler; every sentence earns its place.

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 create tool with no output schema and annotations covering the mutation profile, the description supplies the essential context (what a Function is, the dry-run gate). The only gap is that it says nothing about the returned artifact (e.g., the new function's ID) or that code/name are the meaningful inputs, which an agent might want before calling.

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%, so the schema already documents all four parameters including dryRun and the trigger_function runtime-input note. The description largely restates the dryRun semantics rather than adding syntax or format detail beyond the schema, which is the expected baseline case.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Creates a new Cognigy.AI Function') and adds a one-line definition of what a Function is (custom code modules for integrations, scheduled jobs, computations). The resource is unambiguous, though it never names the neighbouring update_function/get_function/delete_function tools to sharpen the boundary.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by the verb 'creates', and the description usefully flags that you must set dryRun=false for the call to actually take effect. However, it offers no when-to-use guidance relative to update_function (modify existing) or create_package/create_node, leaving the agent to infer the 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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