cognigy-ai-mcp-management-server

get_function_instance

Read-onlyIdempotent

Retrieve detailed information about a specific function instance, including execution status, timing, input, and output or error details.

Instructions

Gets detailed information about a specific Cognigy.AI Function instance. Returns execution status, timing, input parameters, and output/error.

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": {
      "functionId": "<functionId>",
      "functionInstanceId": "<functionInstanceId>"
    },
    "name": "get_function_instance"
  }
}

Input Schema

Name	Required	Description	Default
`functionId`	Yes	The function ID
`functionInstanceId`	Yes	The function instance ID to retrieve

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.4Jul 27, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds concrete return details (execution status, timing, input, output/error), which enhances transparency beyond what annotations alone provide. No contradictions.

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 (20 words) efficiently convey purpose and return contents. Front-loaded with the core action and resource. No wasted words.

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 the tool's simplicity (2 required params, no output schema, full annotations), the description is complete. It explains what the tool does, what it returns, and leaves no ambiguity. No need for additional context.

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%: both required parameters (functionId, functionInstanceId) have descriptions. The description does not add extra parameter semantics beyond the schema, 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 it retrieves detailed information about a specific Cognigy.AI Function instance, listing return fields (execution status, timing, input parameters, output/error). This distinguishes it from sibling list_function_instances (which lists multiple) and get_function (which gets function metadata).

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 clear context for use: retrieving details of a specific function instance. While it doesn't explicitly state when not to use it or name alternatives, the sibling context makes the purpose obvious. The lack of exclusions prevents a perfect 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server