cognigy-ai-mcp-management-server

list_knowledge_sources

Read-onlyIdempotent

List documents and web pages ingested into a knowledge store for RAG retrieval, with pagination and filtering.

Instructions

Lists knowledge sources in a Cognigy.AI knowledge store. Sources are documents (PDFs, web pages, text files) that have been ingested and chunked for RAG retrieval.

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>"
    },
    "name": "list_knowledge_sources"
  }
}

Input Schema

Name	Required	Description
`skip`	No	Number of items to skip for pagination
`limit`	No	Maximum number of sources to return (default: 25, max: 100)
`filter`	No	Filter sources by name
`knowledgeStoreId`	Yes	The knowledge store ID to list sources from

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.4Jul 27, 2026

TDQS

A3.6/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows it's a safe read operation. The description adds context about the nature of sources (ingested and chunked for RAG retrieval), which is helpful but not critical. It does not disclose additional behavioral traits like pagination behavior or rate limits, but annotations cover the safety profile adequately.

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 two sentences, with no wasted words. It is front-loaded with the core purpose, then provides additional context. Every sentence adds value.

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 has 4 parameters, full schema coverage, and no output schema, the description adequately explains the purpose and the nature of sources. However, it does not describe the return format or pagination behavior beyond what schema provides. For a list tool, this is a minor gap but overall sufficient.

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%, meaning all parameters (skip, limit, filter, knowledgeStoreId) have descriptions in the schema. The tool description does not add any extra meaning beyond what is already in the schema. Therefore, the baseline score of 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 the verb 'lists', the resource 'knowledge sources', and the context 'in a Cognigy.AI knowledge store'. It also explains what sources are (documents, PDFs, web pages, text files) and their purpose (ingested and chunked for RAG retrieval). This distinguishes the tool from siblings like list_knowledge_stores or get_knowledge_source.

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

Usage Guidelines2/5

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

The description does not provide any guidance on when to use this tool versus alternatives. It lacks explicit statements about when to use it, when not to use it, or any comparison to sibling tools like get_knowledge_source or list_knowledge_chunks.

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

Deploy Server