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Rubrik MCP

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by rubrikinc

rsc_search_help

Read-only

Search Rubrik KB articles, product documentation, and known issues to troubleshoot RSC errors and answer 'how do I' questions. Returns titles, snippets, and direct links.

Instructions

Search Rubrik KB articles, product documentation, and known issues.

Use when: an RSC event or workload has a failure/error message, the user asks a troubleshooting or "how do I" question, or an error code (e.g. RBK91030123) is present. Always call this before answering from memory — KB articles reflect the current product state. Results include title, description snippet, source type, and a direct link to the full article.

Args: query: Free-text search string (e.g. "ransomware recovery", "SLA not applying"). source: Limit results to one source. One of: KB_ARTICLES, PRODUCT_DOCS, KNOWN_ISSUES. Omit to search all sources. limit: Maximum number of results to return. Default 10.

Returns: A dict with count (total matches), returned (how many results are in this response), truncated (True when more results exist than were returned), and results (list of items with title, source, description, and link). Report count for "how many" questions, not len(results). Note: link may be null for some results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes
sourceNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already confirm it is a safe read (readOnlyHint=true, destructiveHint=false). The description adds important behavioral context beyond the annotations: that KB articles reflect current product state, that results may be truncated, and that links can be null. The main minor gap is no mention of pagination 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

It is front-loaded with purpose and usage guidelines, then structured into Args and Returns sections. Every sentence is useful, though the response is slightly longer than strictly necessary with its formatting.

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?

Given there is no output schema, the description appropriately explains the return structure, including count/returned/truncated/results and the null-link caveat. It is complete enough for an agent to call and interpret results correctly.

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

Parameters5/5

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

Schema description coverage is 0%, so the description carries the full burden. It fully documents all three parameters, including examples and the enum-like values for source and the default for limit, compensating completely for the schema 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 states a specific verb and resource: 'Search Rubrik KB articles, product documentation, and known issues.' This clearly distinguishes it from API/schema exploration siblings like rsc_search_schema or rsc_describe_type, which serve a different purpose.

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

Usage Guidelines5/5

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

It provides explicit when-to-use triggers: an event/workload has an error, a troubleshooting/how-do-I question, or an error code is present. It also gives a strong directive: 'Always call this before answering from memory,' which is a clear usage policy.

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