list_readersList readers (knowledge-base end users / audience accounts). KnowledgeOwl API: GET /reader.json. Returns { valid, page_stats, data:[...] }.
| Name | Required | Description | Default |
|---|---|---|---|
| _page | No | KnowledgeOwl pagination page number, 1-based. | |
| params | No | Additional documented query-string filters/operators to send verbatim (merged with the typed params above). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, covering the safety profile. The description adds the exact API endpoint and the response shape ({ valid, page_stats, data:[...] }), providing useful behavioral context beyond the annotation, though it does not cover pagination behavior or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences front-load the purpose, then add the API endpoint and return shape. There is no filler; every clause contributes useful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only list operation with 0 required parameters, the description plus schema cover the essentials. The return shape is disclosed, and the schema documents the optional parameters. Missing details like pagination field mapping are minor given the low complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%: both _page and params have descriptions in the input schema. The description adds no parameter-level details, so 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.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource ('List readers'), clarifies what 'readers' means ('knowledge-base end users / audience accounts'), and names the exact API endpoint. This makes it clearly distinguishable from sibling list_* tools and get_reader.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by the name and the 'List readers' phrasing, but there is no explicit guidance on when to choose this tool over alternatives like get_reader or knowledgeowl_request. No exclusion criteria or alternative tooling is mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose targeting a specific resource (article, category, glossary, etc.) and action (create, get, list, update). There is no ambiguity or overlap between tool names.
All tools follow a consistent verb_noun pattern: create_X, get_X, list_X, update_X. The exception 'knowledgeowl_request' is a utility escape hatch, clearly marked, and does not break the overall pattern.
At 24 tools, the set is slightly above the typical 3-15 range but still well-scoped for a knowledge base API covering many resources. Each tool serves a distinct purpose, and no tools are redundant.
The tool set lacks delete operations for all resources, and update operations are only available for articles and categories. Missing get tools for glossary terms, snippets, and other resources, though list tools are provided. This leaves significant gaps in lifecycle coverage.