skill-aws-knowledge-tool

dnvriend's avatarfrom dnvriend

CLI tool for querying AWS Knowledge MCP Server

⭐0stars🔀0forks📁View on GitHub🕐Updated Dec 5, 2025⬇️1downloads
[Knowledge Base]

When & Why to Use This Skill

This Claude skill provides a specialized CLI interface for the AWS Knowledge MCP Server, enabling users to programmatically search, retrieve, and convert official AWS documentation into clean Markdown format. It is designed to streamline technical research and documentation discovery for developers and cloud architects, offering structured access to the vast AWS knowledge ecosystem directly within an AI-powered workflow.

Use Cases

  • Technical Research: Perform full-text searches across AWS documentation, blogs, and architecture centers to find specific configuration details or service limits.
  • Documentation Management: Fetch and convert complex AWS documentation pages into Markdown for inclusion in internal wikis, project READMEs, or technical notes.
  • Architecture Optimization: Discover related AWS services and best practices using the 'recommend' feature to explore similar topics, new features, and common user journeys.
  • DevOps Automation: Integrate AWS knowledge retrieval into automated scripts or CI/CD pipelines using JSON output for programmatic technical audits or information gathering.
nameskill-aws-knowledge-tool
descriptionCLI tool for querying AWS Knowledge MCP Server

When to use

  • When you need to search AWS documentation programmatically
  • When you need to read and convert AWS docs to markdown
  • When you need to discover related AWS documentation

AWS Knowledge Tool Skill

Purpose

This skill provides access to the aws-knowledge-tool CLI - a command-line interface for querying the AWS Knowledge MCP Server. Use it to search, read, and discover AWS documentation programmatically.

When to Use This Skill

Use this skill when:

  • You need to search AWS documentation with full-text search
  • You need to read AWS documentation pages as markdown
  • You need to discover related documentation recommendations
  • You need structured/JSON output for processing

Do NOT use this skill for:

  • Writing new AWS documentation (read-only)
  • Deploying AWS resources (documentation only)
  • AWS CLI operations (use AWS CLI instead)

CLI Tool: aws-knowledge-tool

The aws-knowledge-tool is a CLI tool for querying the AWS Knowledge MCP Server to search, read, and discover AWS documentation.

Installation

# Clone and install
git clone https://github.com/dnvriend/aws-knowledge-tool.git
cd aws-knowledge-tool
uv tool install .

Prerequisites

  • Python 3.14+
  • uv package manager

Quick Start

# Search AWS documentation
aws-knowledge-tool search "Lambda function URLs"

# Read documentation page
aws-knowledge-tool read "https://docs.aws.amazon.com/lambda/latest/dg/welcome.html"

# Get recommendations
aws-knowledge-tool recommend "https://docs.aws.amazon.com/lambda/latest/dg/welcome.html"

Progressive Disclosure

📖 Core Commands (Click to expand)

search - Search AWS Documentation

Search across AWS documentation, blogs, solutions library, architecture center, and prescriptive guidance.

Usage:

aws-knowledge-tool search QUERY [OPTIONS]

Arguments:

  • QUERY: Search query text (required)
  • --limit N / -l N: Maximum results (default: 10)
  • --offset M / -o M: Skip first M results for pagination (default: 0)
  • --json: Output JSON format for processing
  • --stdin: Read query from stdin (for pipelines)
  • -v/-vv/-vvv: Verbosity (INFO/DEBUG/TRACE)

Examples:

# Basic search
aws-knowledge-tool search "S3 versioning"

# With pagination
aws-knowledge-tool search "Lambda" --limit 10 --offset 20

# JSON output
aws-knowledge-tool search "DynamoDB" --json

# Pipeline usage
echo "CloudFormation" | aws-knowledge-tool search --stdin --json

Output: Returns list of results with: title, url, context, rank_order

read - Read AWS Documentation

Fetch and convert AWS documentation pages to markdown format.

Usage:

aws-knowledge-tool read URL [OPTIONS]

Arguments:

  • URL: AWS documentation URL (required)
  • --start-index N / -s N: Starting character index for pagination
  • --max-length M / -m M: Maximum characters to fetch
  • --json: Output JSON format
  • --stdin: Read URL from stdin
  • -v/-vv/-vvv: Verbosity (INFO/DEBUG/TRACE)

Examples:

# Read full document
aws-knowledge-tool read "https://docs.aws.amazon.com/lambda/latest/dg/welcome.html"

# With pagination (large docs)
aws-knowledge-tool read "https://docs.aws.amazon.com/..." \
  --start-index 5000 --max-length 2000

# Pipeline from search
aws-knowledge-tool search "Lambda" --json | \
  jq -r '.[0].url' | \
  aws-knowledge-tool read --stdin

Output: Returns markdown-formatted documentation content.

Supported domains:

  • docs.aws.amazon.com
  • aws.amazon.com

recommend - Get Documentation Recommendations

Discover related documentation through four recommendation types.

Usage:

aws-knowledge-tool recommend URL [OPTIONS]

Arguments:

  • URL: AWS documentation URL (required)
  • --type TYPE / -t TYPE: Filter by recommendation type
    • highly_rated: Popular pages within same AWS service
    • new: Recently added pages (useful for finding new features)
    • similar: Pages covering similar topics
    • journey: Pages commonly viewed next by other users
  • --limit N / -l N: Max results per category (default: 5)
  • --offset M / -o M: Skip first M per category (default: 0)
  • --json: Output JSON format
  • --stdin: Read URL from stdin
  • -v/-vv/-vvv: Verbosity (INFO/DEBUG/TRACE)

Examples:

# Get all recommendations
aws-knowledge-tool recommend "https://docs.aws.amazon.com/lambda/latest/dg/welcome.html"

# Filter by type (find new features)
aws-knowledge-tool recommend "https://docs.aws.amazon.com/..." --type new

# JSON output with limit
aws-knowledge-tool recommend "https://docs.aws.amazon.com/..." --json --limit 3

# Pipeline usage
aws-knowledge-tool search "Lambda" --json | \
  jq -r '.[0].url' | \
  aws-knowledge-tool recommend --stdin --type similar

Output: Returns dict with recommendation categories and their pages (title, url, context).

⚙️ Advanced Features (Click to expand)

Multi-Level Verbosity Logging

Control logging detail with progressive verbosity levels. All logs output to stderr.

Logging Levels:

Flag Level Output Use Case
(none) WARNING Errors and warnings only Production, quiet mode
-v INFO + High-level operations Normal debugging
-vv DEBUG + Detailed info, full tracebacks Development, troubleshooting
-vvv TRACE + Library internals Deep debugging

Examples:

# INFO level - see operations
aws-knowledge-tool search "Lambda" -v

# DEBUG level - see detailed info
aws-knowledge-tool search "Lambda" -vv

# TRACE level - see all internals
aws-knowledge-tool search "Lambda" -vvv

Shell Completion

Native shell completion for bash, zsh, and fish.

Installation:

# Bash (add to ~/.bashrc)
eval "$(aws-knowledge-tool completion bash)"

# Zsh (add to ~/.zshrc)
eval "$(aws-knowledge-tool completion zsh)"

# Fish (save to completions)
aws-knowledge-tool completion fish > ~/.config/fish/completions/aws-knowledge-tool.fish

Pipeline Composition

Compose commands with Unix pipes for powerful workflows.

Examples:

# Search → Extract URL → Read
aws-knowledge-tool search "Lambda" --json | \
  jq -r '.[0].url' | \
  aws-knowledge-tool read --stdin

# Search → Extract URL → Get similar docs
aws-knowledge-tool search "S3" --json | \
  jq -r '.[0].url' | \
  aws-knowledge-tool recommend --stdin --type similar

# Save search results to file
aws-knowledge-tool search "DynamoDB" --json > results.json

# Read and save as markdown
aws-knowledge-tool read "https://docs.aws.amazon.com/..." > lambda-docs.md
🔧 Troubleshooting (Click to expand)

Common Issues

Issue: Command not found

# Verify installation
aws-knowledge-tool --version

# Reinstall if needed
cd aws-knowledge-tool
uv tool install . --reinstall

Issue: No results from search

  • Check your search query is specific enough
  • Try broader search terms
  • Use --json to see full response

Issue: URL validation error

  • Ensure URL is from docs.aws.amazon.com or aws.amazon.com
  • Check URL is accessible in browser first

Issue: Connection timeout

  • Check internet connection
  • AWS Knowledge MCP Server may be temporarily unavailable
  • Try again with verbose flag: -vv

Getting Help

# Show help
aws-knowledge-tool --help

# Command-specific help
aws-knowledge-tool search --help
aws-knowledge-tool read --help
aws-knowledge-tool recommend --help

Exit Codes

  • 0: Success
  • 1: Client error (invalid arguments, validation failed)
  • 2: Server error (API error, network issue)
  • 3: Network error (connection failed, timeout)

Output Formats

Default (Markdown):

  • Human-readable formatted output
  • Search: ranked list with titles, URLs, context
  • Read: markdown content
  • Recommend: grouped by category with titles, URLs

JSON (--json flag):

  • Machine-readable structured data
  • Perfect for pipelines and processing
  • Consistent structure across commands

Best Practices

  1. Use JSON for pipelines: Enable --json when piping to other tools
  2. Pagination for large results: Use --limit and --offset for controlled fetching
  3. Progressive verbosity: Start with -v, increase to -vv/-vvv only if needed
  4. Save frequent searches: Cache JSON results to avoid repeated API calls
  5. Compose commands: Leverage Unix pipes for powerful workflows

Resources