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Unilytics MCP Server

Unilytics MCP Server

Official
by TeamUnilytics
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

kb_get_status

Read-only

Check a knowledge base's indexing status with total, ready, pending, and failed counts plus per-document status, so you can confirm which documents are searchable and why failures occurred.

Instructions

Get a KB's indexing status: total/ready/pending/failed counts and per-document status. Writes are ingested in the background, and kb_search returns only 'ready' documents. A 'failed' document's error says why it failed. The counts cover the whole KB; documents is one page, and next_cursor (when set) is passed back as cursor for the next page.

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": {
      "project_id": "<project_id>",
      "collection_id": "<collection_id>"
    },
    "name": "kb_get_status"
  }
}

Input Schema

NameRequiredDescriptionDefault
cursorNo
project_idYes
collection_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.1.0
    • removedInput schema / properties / config
      Removed value: -{
-  "default": null,
-  "title": "config",
-  "type": "string"
-}
    • addedInput schema / properties / cursor
      Added value: +{
+  "default": null,
+  "title": "Cursor",
+  "type": "string"
+}
  2. First observedv1.0.0

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already establish readOnly/openWorld=false/destructive=false, but the description adds substantial behavior the annotations cannot convey: asynchronous background ingestion, the fact that kb_search sees only 'ready' documents, that 'failed' documents carry an `error` reason, and that counts are KB-wide while `documents` is paginated. This is exactly the kind of context an agent needs to interpret results correctly.

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?

Four compact sentences, front-loaded with purpose, then result shape, then ingestion semantics, then pagination. No filler or restated name/title; each sentence adds information.

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?

There is no output schema, so the description must describe return values, and it does: counts, per-document status, the `error` field on failures, and the documents/next_cursor pagination contract. Nothing essential for correct invocation or interpretation is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description carries the burden; it explains the non-obvious `cursor` parameter by tying it to `next_cursor` from a prior page. It does not explain project_id or collection_id, but those are self-evident identifiers given the KB framing, leaving only a minor gap.

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 opens with a specific verb and resource ('Get a KB's indexing status') and enumerates exactly what comes back: total/ready/pending/failed counts plus per-document status. It also implicitly separates this tool from kb_search by noting that search only surfaces 'ready' documents, so an agent can tell the two apart without inspecting schemas.

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?

Usage is clearly implied: writes are ingested in the background, so this is the tool to check after a write, and kb_search is the alternative once documents are ready. It does not state explicit exclusions or point to kb_get_document for single-document detail, so it stops short of full when/when-not guidance.

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

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