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Rebranding, refactoring, renaming, cleanup, updated docs

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Fahad
2025-06-12 10:40:43 +04:00
parent 9a55ca8898
commit fb66825bf6
55 changed files with 1048 additions and 1474 deletions
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11
config.py
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@@ -1,7 +1,7 @@
"""
Configuration and constants for Gemini MCP Server
Configuration and constants for Zen MCP Server
This module centralizes all configuration settings for the Gemini MCP Server.
This module centralizes all configuration settings for the Zen MCP Server.
It defines model configurations, token limits, temperature defaults, and other
constants used throughout the application.
@@ -29,8 +29,11 @@ DEFAULT_MODEL = os.getenv("DEFAULT_MODEL", "auto")
VALID_MODELS = ["auto", "flash", "pro", "o3", "o3-mini", "gemini-2.0-flash-exp", "gemini-2.5-pro-preview-06-05"]
if DEFAULT_MODEL not in VALID_MODELS:
import logging
logger = logging.getLogger(__name__)
logger.warning(f"Invalid DEFAULT_MODEL '{DEFAULT_MODEL}'. Setting to 'auto'. Valid options: {', '.join(VALID_MODELS)}")
logger.warning(
f"Invalid DEFAULT_MODEL '{DEFAULT_MODEL}'. Setting to 'auto'. Valid options: {', '.join(VALID_MODELS)}"
)
DEFAULT_MODEL = "auto"
# Auto mode detection - when DEFAULT_MODEL is "auto", Claude picks the model
@@ -45,7 +48,7 @@ MODEL_CAPABILITIES_DESC = {
"o3-mini": "Fast O3 variant (200K context) - Balanced performance/speed, moderate complexity",
# Full model names also supported
"gemini-2.0-flash-exp": "Ultra-fast (1M context) - Quick analysis, simple queries, rapid iterations",
"gemini-2.5-pro-preview-06-05": "Deep reasoning + thinking mode (1M context) - Complex problems, architecture, deep analysis"
"gemini-2.5-pro-preview-06-05": "Deep reasoning + thinking mode (1M context) - Complex problems, architecture, deep analysis",
}
# Token allocation for Gemini Pro (1M total capacity)