cognigy-ai-mcp-management-server

create_knowledge_chunk

Add specific text segments to a Cognigy.AI knowledge store as searchable chunks for RAG. Set dryRun=false to create.

Instructions

Creates a new Cognigy.AI knowledge chunk manually. Use this to add specific text segments that should be searchable via RAG. The chunk will be embedded automatically. 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": {
      "knowledgeStoreId": "<knowledgeStoreId>",
      "sourceId": "<sourceId>",
      "text": "<text>"
    },
    "name": "create_knowledge_chunk"
  }
}

Input Schema

Name	Required	Description
`text`	Yes	The text content of the chunk
`title`	No	Title for the chunk
`dryRun`	No	If true (default), validates without creating. Set to false to actually create.
`metadata`	No	Custom metadata for the chunk
`sourceId`	Yes	The source ID to associate the chunk with
`knowledgeStoreId`	Yes	The knowledge store ID to create the chunk in

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.4Jul 27, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Annotations already indicate mutating (readOnlyHint=false). The description adds value by stating the chunk will be 'embedded automatically' and that dryRun=false performs actual creation, providing behavioral context beyond 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?

Three concise sentences: purpose, usage context, and mutation hint. Each sentence is essential, front-loads key information, and avoids unnecessary detail.

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?

With 6 parameters and no output schema, the description covers purpose, usage context, and the dryRun mechanism, but lacks detail on return values, authorization needs, or duplicate handling. Adequate for a creation tool but 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 description coverage is 100%, so the schema already documents all parameters. The description adds minimal semantic value beyond repeating dryRun behavior; it does not elaborate on nested objects or metadata constraints.

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 new Cognigy.AI knowledge chunk manually') and the resource ('knowledge chunk'). It distinguishes the tool from siblings like list/update/delete knowledge chunks by specifying manual creation and RAG searchability.

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?

Describes when to use (add text segments for RAG) and hints at the dryRun parameter for safe validation, but does not explicitly state when not to use or compare with alternatives (e.g., update or delete chunks). No exclusion criteria provided.

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

Deploy Server