feat: Claude desktop and Amazon Q CLI integration #6
+562
β289
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π Pull Request
π Description
Brief description of changes and motivation.
Features Added:
β’ STDIO Transport Entry Point - Added
main_stdio.pyfor Claude Desktop and Amazon Q CLI integration using official MCP SDKβ’ Claude Desktop Integration - Complete setup guide with configuration examples and 6 core analysis tools
β’ Amazon Q CLI Integration - Command-line Spark analysis with batch processing capabilities and automation examples
β’ Multi-Transport Architecture - Preserves existing FastMCP HTTP server while adding STDIO support for different client types
Improvements:
β’ Simplified Documentation - Consolidated scattered setup instructions into single clear paths
β’ Taskfile Integration - Updated all docs to use consistent task commands instead of mixed uv/shell scripts
β’ Tool Clarity - Clear distinction between 6 core STDIO tools vs 18 comprehensive HTTP tools
β’ Remote Server Support - Configuration guidance for connecting to production Spark History Servers
Fixes:
β’ Pre-commit Integration - Fixed Taskfile to use uv run pre-commit for consistent developer experience
β’ Code Quality - Resolved linting issues (bare except clauses, print statements) in STDIO entry point
β’ Path Resolution - Realistic path examples and clear replacement instructions for different environments
Docs:
β’ Removed Duplication - Eliminated redundant setup sections between main README and testing docs
β’ Streamlined Testing - Simplified TESTING.md from 3 approaches to 1 recommended path
β’ Integration Comparison - Added clear table showing transport types, entry points, and use cases
β’ Prerequisites Cleanup - Moved detailed setup to individual integration docs, kept main README focused
π― Type of Change
π§ͺ Testing
task test)π¬ Test Commands Run
π οΈ New Tools Added (if applicable)
new_tool_nameπΈ Screenshots (if applicable)
β Checklist
π Related Issues
Fixes #(issue number)
Related to #(issue number)
π€ Additional Context
π Thank you for contributing! Your effort helps make Spark monitoring more intelligent.