27add4d05d
## 🚀 Major Improvements ### Docker Environment Simplification - **BREAKING**: Simplified Docker configuration by auto-detecting sandbox from WORKSPACE_ROOT - Removed redundant MCP_PROJECT_ROOT requirement for Docker setups - Updated all Docker config examples and setup scripts - Added security validation for dangerous WORKSPACE_ROOT paths ### Security Enhancements - **CRITICAL**: Fixed insecure PROJECT_ROOT fallback to use current directory instead of home - Enhanced path validation with proper Docker environment detection - Removed information disclosure in error messages - Strengthened symlink and path traversal protection ### File Handling Optimization - **PERFORMANCE**: Optimized read_files() to return content only (removed summary) - Unified file reading across all tools using standardized file_utils routines - Fixed review_changes tool to use consistent file loading patterns - Improved token management and reduced unnecessary processing ### Tool Improvements - **UX**: Enhanced ReviewCodeTool to require user context for targeted reviews - Removed deprecated _get_secure_container_path function and _sanitize_filename - Standardized file access patterns across analyze, review_changes, and other tools - Added contextual prompting to align reviews with user expectations ### Code Quality & Testing - Updated all tests for new function signatures and requirements - Added comprehensive Docker path integration tests - Achieved 100% test coverage (95 tests passing) - Full compliance with ruff, black, and isort linting standards ### Configuration & Deployment - Added pyproject.toml for modern Python packaging - Streamlined Docker setup removing redundant environment variables - Updated setup scripts across all platforms (Windows, macOS, Linux) - Improved error handling and validation throughout ## 🔧 Technical Changes - **Removed**: `_get_secure_container_path()`, `_sanitize_filename()`, unused SANDBOX_MODE - **Enhanced**: Path translation, security validation, token management - **Standardized**: File reading patterns, error handling, Docker detection - **Updated**: All tool prompts for better context alignment ## 🛡️ Security Notes This release significantly improves the security posture by: - Eliminating broad filesystem access defaults - Adding validation for Docker environment variables - Removing information disclosure in error paths - Strengthening path traversal and symlink protections 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
52 lines
2.4 KiB
Python
52 lines
2.4 KiB
Python
"""
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Configuration and constants for Gemini MCP Server
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This module centralizes all configuration settings for the Gemini MCP Server.
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It defines model configurations, token limits, temperature defaults, and other
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constants used throughout the application.
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Configuration values can be overridden by environment variables where appropriate.
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"""
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# Version and metadata
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# These values are used in server responses and for tracking releases
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__version__ = "2.11.0" # Semantic versioning: MAJOR.MINOR.PATCH
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__updated__ = "2025-06-10" # Last update date in ISO format
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__author__ = "Fahad Gilani" # Primary maintainer
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# Model configuration
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# GEMINI_MODEL: The Gemini model used for all AI operations
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# This should be a stable, high-performance model suitable for code analysis
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GEMINI_MODEL = "gemini-2.5-pro-preview-06-05"
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# MAX_CONTEXT_TOKENS: Maximum number of tokens that can be included in a single request
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# This limit includes both the prompt and expected response
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# Gemini Pro models support up to 1M tokens, but practical usage should reserve
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# space for the model's response (typically 50K-100K tokens reserved)
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MAX_CONTEXT_TOKENS = 1_000_000 # 1M tokens for Gemini Pro
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# Temperature defaults for different tool types
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# Temperature controls the randomness/creativity of model responses
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# Lower values (0.0-0.3) produce more deterministic, focused responses
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# Higher values (0.7-1.0) produce more creative, varied responses
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# TEMPERATURE_ANALYTICAL: Used for tasks requiring precision and consistency
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# Ideal for code review, debugging, and error analysis where accuracy is critical
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TEMPERATURE_ANALYTICAL = 0.2 # For code review, debugging
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# TEMPERATURE_BALANCED: Middle ground for general conversations
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# Provides a good balance between consistency and helpful variety
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TEMPERATURE_BALANCED = 0.5 # For general chat
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# TEMPERATURE_CREATIVE: Higher temperature for exploratory tasks
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# Used when brainstorming, exploring alternatives, or architectural discussions
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TEMPERATURE_CREATIVE = 0.7 # For architecture, deep thinking
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# MCP Protocol Limits
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# MCP_PROMPT_SIZE_LIMIT: Maximum character size for prompts sent directly through MCP
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# The MCP protocol has a combined request+response limit of ~25K tokens.
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# To ensure we have enough space for responses, we limit direct prompt input
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# to 50K characters (roughly ~10-12K tokens). Larger prompts must be sent
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# as files to bypass MCP's token constraints.
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MCP_PROMPT_SIZE_LIMIT = 50_000 # 50K characters
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