Major improvements to thinking capabilities and API integration:
- Remove all output token limits for future-proof responses
- Add 5-level thinking mode system: minimal, low, medium, high, max
- Migrate from google-generativeai to google-genai library
- Implement native thinkingBudget support for Gemini 2.5 Pro
- Set medium thinking as default for all tools, max for think_deeper
🧠 Thinking Modes:
- minimal (128 tokens) - simple tasks
- low (2048 tokens) - basic reasoning
- medium (8192 tokens) - default for most tools
- high (16384 tokens) - complex analysis
- max (32768 tokens) - default for think_deeper
🔧 Technical Changes:
- Complete migration to google-genai>=1.19.0
- Remove google-generativeai dependency
- Add ThinkingConfig with thinking_budget parameter
- Update all tools to support thinking_mode parameter
- Comprehensive test suite with 37 passing unit tests
- CI-friendly testing (no API key required for unit tests)
- Live integration tests for API verification
🧪 Testing & CI:
- Add GitHub Actions workflow with multi-Python support
- Unit tests use mocks, no API key required
- Live integration tests optional with API key
- Contributing guide with development setup
- All tests pass without external dependencies
🐛 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
Major redesign of Gemini MCP Server with modular architecture:
- Removed all emoji characters from tool outputs for clean terminal display
- Kept review category emojis (🔴🟠🟡🟢) per user preference
- Added 4 specialized tools:
- think_deeper: Extended reasoning and problem-solving (temp 0.7)
- review_code: Professional code review with severity levels (temp 0.2)
- debug_issue: Root cause analysis and debugging (temp 0.2)
- analyze: General-purpose file analysis (temp 0.2)
- Modular architecture with base tool class and Pydantic models
- Verbose tool descriptions with natural language triggers
- Updated README with comprehensive examples and real-world use cases
- All 25 tests passing, type checking clean, critical linting clean
BREAKING CHANGE: Removed analyze_code tool in favor of specialized tools
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
Added professional testing infrastructure:
Unit Tests:
- Comprehensive test suite covering all major functionality
- Tests for models, file operations, tool handlers, and error cases
- Async test support for MCP handlers
- Mocking for external API calls
- 84% code coverage achieved
CI/CD Pipeline:
- GitHub Actions workflow for automated testing
- Matrix testing across Python 3.8-3.12
- Cross-platform testing (Ubuntu, macOS, Windows)
- Automated linting with flake8, black, isort, and mypy
- Code coverage reporting with 80% minimum threshold
Configuration:
- pytest.ini with proper test discovery and coverage settings
- .coveragerc for coverage configuration
- Updated .gitignore for test artifacts
- Development dependencies in requirements.txt
Documentation:
- Added testing section to README
- Instructions for running tests locally
- Contributing guidelines with test requirements
This ensures code quality and reliability for all contributions.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- MCP server implementation for Google Gemini models
- Support for multiple Gemini models including 1.5 Pro and 2.5 Pro preview
- Chat tool with configurable parameters (temperature, max_tokens, model)
- List models tool to view available Gemini models
- System prompt support
- Comprehensive error handling for blocked responses
- Test suite included
- Documentation and examples
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
