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Docs Navigator MCP - SUSE Edition

Docs Navigator MCP - SUSE Edition

by mso-docs
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
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search_docs

Search SUSE, Rancher, and K3s documentation using semantic search to find relevant sections.

Instructions

Search SUSE, Rancher, K3s, and related documentation using semantic search. Returns relevant documentation sections.

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": {
      "query": "<query>"
    },
    "name": "search_docs"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum number of results to return (default: 5)
queryYesThe search query to find relevant documentation
sourceNoOptional: Filter by documentation source (suse, rancher, k3s, all)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description must carry the burden of behavioral disclosure. It mentions 'semantic search' and returns 'relevant documentation sections,' which gives some idea of behavior, but it doesn't disclose potential rate limits, authentication needs, whether results are snippets or full text, or whether any other side effects exist. It's minimal but not misleading.

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?

Two sentences, no wasted words. The first sentence is front-loaded with the action ('Search'), and the second explains the return type. Every word earns its place.

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?

For a simple 3-parameter search tool, the description is adequate but leaves gaps. It doesn't clarify the output format (e.g., URLs, titles, snippets) or how the optional source filter works. Given the sibling get_doc_section, it would help to state that search returns results that may be retrieved with get_doc_section. Still, the tool is simple enough that this is acceptable.

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 coverage is 100% with parameter descriptions for query, limit, and source. The description adds no extra parameter semantics, so baseline 3 applies. It doesn't explain how the source filter interacts with the search or what the limit controls beyond the schema's description.

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 tool performs a semantic search over specific documentation sets (SUSE, Rancher, K3s) and returns relevant sections. This is a specific verb-resource pair that differentiates it from siblings like get_doc_section (retrieving a section) or summarize_doc (summarizing), even though it doesn't explicitly name them.

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?

No guidance is given on when to use this tool versus alternatives. It doesn't mention exclusions like 'use get_doc_section for retrieving a known section' or 'use ask_question for natural-language questions.' The context implies it's for discovery, but sibling differentiation is absent.

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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