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Joseph19820124

AWS Documentation MCP Server

search_documentation

Search across all AWS documentation using the official API to find pages matching your search phrase. Get results with URLs, titles, and context snippets for quick reference.

Instructions

Search AWS documentation using the official AWS Documentation Search API.

## Usage

This tool searches across all AWS documentation for pages matching your search phrase.
Use it to find relevant documentation when you don't have a specific URL.

## Search Tips

- Use specific technical terms rather than general phrases
- Include service names to narrow results (e.g., "S3 bucket versioning" instead of just "versioning")
- Use quotes for exact phrase matching (e.g., "AWS Lambda function URLs")
- Include abbreviations and alternative terms to improve results

## Result Interpretation

Each result includes:
- rank_order: The relevance ranking (lower is more relevant)
- url: The documentation page URL
- title: The page title
- context: A brief excerpt or summary (if available)

Args:
    ctx: MCP context for logging and error handling
    search_phrase: Search phrase to use
    limit: Maximum number of results to return

Returns:
    List of search results with URLs, titles, and context snippets

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results to return
search_phraseYesSearch phrase to use
Behavior4/5

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

No annotations, so description carries the burden. It describes the API source and result structure but does not explicitly state it's read-only or idempotent. However, as a search tool, this is implied. Adds value with result interpretation.

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?

Well-structured with sections (Usage, Search Tips, Result Interpretation). Each section is meaningful. Slightly lengthy but no wasted sentences.

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 the tool's complexity (search across all docs) and no output schema, the description fully explains input parameters, result format, and usage tips. Sufficient for correct invocation.

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 covers 100% of parameters, but the description adds search tips for search_phrase and explains limit's default and range. Also describes return fields, adding meaning beyond schema.

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 it searches AWS documentation using the official API. It distinguishes from read_documentation (which likely uses a URL) and recommend. The verb 'search' and resource 'documentation' are specific.

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?

Explicitly says 'Use it to find relevant documentation when you don't have a specific URL.' Provides search tips (specific terms, service names, quotes) that guide effective use.

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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