cognigy-ai-mcp-management-server

get_transcript

Read-onlyIdempotent

Retrieve a chronological transcript of a Cognigy.AI session showing the user-bot conversation flow for reviewing quality or debugging.

Instructions

Assembles a human-readable transcript for a Cognigy.AI session. Shows the conversation flow between user and bot in chronological order. Use this for reviewing conversation quality or debugging.

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": {
      "sessionId": "<sessionId>"
    },
    "name": "get_transcript"
  }
}

Input Schema

Name	Required	Description	Default
`format`	No	Output format: 'full' includes all metadata, 'compact' shows just the conversation flow	compact
`projectId`	No	Optional project ID to scope the query
`sessionId`	Yes	The session ID to get transcript for

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.4Jul 27, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, covering safety. The description adds value by noting the output is human-readable and chronological, which goes beyond annotations. No 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?

Two sentences: first defines purpose, second gives usage context. No fluff, well-structured, and front-loaded.

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 read-only tool with full schema coverage and no output schema, the description adequately explains what it does and when to use it. It does not detail the return format or structure, but 'human-readable' implies a textual representation.

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% with clear descriptions for all three parameters. The description does not add significant extra meaning beyond the schema's field descriptions, meeting the baseline.

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?

The description clearly states the tool assembles a human-readable transcript for a session and shows conversation flow in chronological order. It uses a specific verb ('assembles') and resource ('transcript'). However, it does not explicitly differentiate from sibling tools like get_conversation, which might also retrieve conversation data.

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 gives explicit use cases: 'reviewing conversation quality or debugging.' It implies when to use, but does not mention when not to use or provide alternatives among siblings.

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

Deploy Server