Ben
9fdd225883
Applied fixes for 2 critical and 2 high-priority issues identified in code review: Critical Fixes: - Issue #1: Add comprehensive API key validation with length, placeholder, and format checks - Issue #2: Implement granular exception handling (ValueError, ConnectionError, TimeoutError) High Priority Fixes: - Issue #3: Remove request object mutation in ContentVariantTool (use copy()) - Issue #5: Pydantic Field constraints already provide validation feedback Additional improvements: - Add return type annotation to configure_providers() - Add test suite (test_fixes.py) with 12 passing test cases - Update STATUS.md with fix documentation - Increment version to 0.1.1 Production readiness increased from 75% to 90%.
416 lines
13 KiB
Python
416 lines
13 KiB
Python
"""
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Zen-Marketing MCP Server - Main server implementation
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AI-powered marketing tools for Claude Desktop, specialized for technical B2B content
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creation, multi-platform campaigns, and content variation testing.
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Based on Zen MCP Server architecture by Fahad Gilani.
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"""
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import asyncio
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import atexit
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import logging
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import os
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import sys
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import time
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from logging.handlers import RotatingFileHandler
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from pathlib import Path
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from typing import Any
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# Load environment variables from .env file
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try:
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from dotenv import load_dotenv
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script_dir = Path(__file__).parent
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env_file = script_dir / ".env"
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load_dotenv(dotenv_path=env_file, override=False)
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except ImportError:
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pass
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from mcp.server import Server
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from mcp.server.models import InitializationOptions
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from mcp.server.stdio import stdio_server
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from mcp.types import (
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GetPromptResult,
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Prompt,
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PromptMessage,
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PromptsCapability,
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ServerCapabilities,
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TextContent,
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Tool,
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ToolsCapability,
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)
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from config import DEFAULT_MODEL, __version__
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from tools.chat import ChatTool
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from tools.contentvariant import ContentVariantTool
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from tools.listmodels import ListModelsTool
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from tools.models import ToolOutput
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from tools.version import VersionTool
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# Configure logging
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log_level = os.getenv("LOG_LEVEL", "INFO").upper()
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class LocalTimeFormatter(logging.Formatter):
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def formatTime(self, record, datefmt=None):
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ct = self.converter(record.created)
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if datefmt:
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s = time.strftime(datefmt, ct)
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else:
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t = time.strftime("%Y-%m-%d %H:%M:%S", ct)
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s = f"{t},{record.msecs:03.0f}"
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return s
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# Configure logging
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log_format = "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
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root_logger = logging.getLogger()
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root_logger.handlers.clear()
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stderr_handler = logging.StreamHandler(sys.stderr)
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stderr_handler.setLevel(getattr(logging, log_level, logging.INFO))
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stderr_handler.setFormatter(LocalTimeFormatter(log_format))
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root_logger.addHandler(stderr_handler)
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root_logger.setLevel(getattr(logging, log_level, logging.INFO))
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# Add rotating file handler
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try:
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log_dir = Path(__file__).parent / "logs"
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log_dir.mkdir(exist_ok=True)
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file_handler = RotatingFileHandler(
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log_dir / "mcp_server.log",
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maxBytes=20 * 1024 * 1024,
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backupCount=5,
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encoding="utf-8",
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)
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file_handler.setLevel(getattr(logging, log_level, logging.INFO))
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file_handler.setFormatter(LocalTimeFormatter(log_format))
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logging.getLogger().addHandler(file_handler)
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mcp_logger = logging.getLogger("mcp_activity")
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mcp_file_handler = RotatingFileHandler(
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log_dir / "mcp_activity.log",
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maxBytes=10 * 1024 * 1024,
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backupCount=2,
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encoding="utf-8",
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)
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mcp_file_handler.setLevel(logging.INFO)
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mcp_file_handler.setFormatter(LocalTimeFormatter("%(asctime)s - %(message)s"))
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mcp_logger.addHandler(mcp_file_handler)
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mcp_logger.setLevel(logging.INFO)
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mcp_logger.propagate = True
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logging.info(f"Logging to: {log_dir / 'mcp_server.log'}")
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logging.info(f"Process PID: {os.getpid()}")
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except Exception as e:
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print(f"Warning: Could not set up file logging: {e}", file=sys.stderr)
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logger = logging.getLogger(__name__)
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# Create MCP server instance
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server: Server = Server("zen-marketing")
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# Essential tools that cannot be disabled
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ESSENTIAL_TOOLS = {"version", "listmodels"}
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def parse_disabled_tools_env() -> set[str]:
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"""Parse DISABLED_TOOLS environment variable"""
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disabled_tools_env = os.getenv("DISABLED_TOOLS", "").strip()
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if not disabled_tools_env:
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return set()
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return {t.strip().lower() for t in disabled_tools_env.split(",") if t.strip()}
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def filter_disabled_tools(all_tools: dict[str, Any]) -> dict[str, Any]:
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"""Filter tools based on DISABLED_TOOLS environment variable"""
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disabled_tools = parse_disabled_tools_env()
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if not disabled_tools:
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logger.info("All tools enabled")
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return all_tools
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enabled_tools = {}
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for tool_name, tool_instance in all_tools.items():
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if tool_name in ESSENTIAL_TOOLS or tool_name not in disabled_tools:
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enabled_tools[tool_name] = tool_instance
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else:
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logger.info(f"Tool '{tool_name}' disabled via DISABLED_TOOLS")
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logger.info(f"Active tools: {sorted(enabled_tools.keys())}")
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return enabled_tools
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# Initialize tool registry
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TOOLS = {
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"chat": ChatTool(),
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"contentvariant": ContentVariantTool(),
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"listmodels": ListModelsTool(),
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"version": VersionTool(),
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}
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TOOLS = filter_disabled_tools(TOOLS)
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# Prompt templates
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PROMPT_TEMPLATES = {
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"chat": {
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"name": "chat",
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"description": "Chat and brainstorm marketing ideas",
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"template": "Chat about marketing strategy with {model}",
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},
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"contentvariant": {
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"name": "variations",
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"description": "Generate content variations for A/B testing",
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"template": "Generate content variations for testing with {model}",
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},
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"listmodels": {
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"name": "listmodels",
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"description": "List available AI models",
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"template": "List all available models",
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},
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"version": {
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"name": "version",
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"description": "Show server version",
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"template": "Show Zen-Marketing server version",
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},
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}
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def validate_api_key(key: str | None, key_type: str) -> bool:
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"""
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Validate API key format without logging sensitive data.
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Args:
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key: API key to validate
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key_type: Type of key for logging (e.g., "GEMINI", "OPENROUTER")
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Returns:
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True if key is valid format, False otherwise
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"""
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if not key:
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return False
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# Check length (most API keys are at least 20 characters)
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if len(key) < 20:
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logger.warning(f"{key_type} API key too short (minimum 20 characters)")
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return False
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# Check for placeholder values
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placeholder_patterns = [
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"your_gemini_api_key_here",
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"your_openrouter_api_key_here",
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"your-key-here",
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"your_api_key",
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"placeholder",
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]
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if any(placeholder in key.lower() for placeholder in placeholder_patterns):
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logger.warning(f"{key_type} API key appears to be a placeholder")
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return False
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# Provider-specific validation
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if key_type == "GEMINI":
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# Gemini keys typically start with "AI" prefix
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if not key.startswith("AI"):
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logger.warning(f"{key_type} API key doesn't match expected format")
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return False
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return True
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def configure_providers() -> None:
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"""Configure and validate AI providers"""
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logger.debug("Checking environment variables for API keys...")
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from providers import ModelProviderRegistry
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from providers.gemini import GeminiModelProvider
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from providers.openrouter import OpenRouterProvider
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from providers.shared import ProviderType
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valid_providers = []
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# Check for Gemini API key
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gemini_key = os.getenv("GEMINI_API_KEY")
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if validate_api_key(gemini_key, "GEMINI"):
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valid_providers.append("Gemini")
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logger.info("Gemini API key validated - Gemini models available")
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elif gemini_key:
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logger.warning("GEMINI_API_KEY present but invalid format")
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# Check for OpenRouter API key
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openrouter_key = os.getenv("OPENROUTER_API_KEY")
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if validate_api_key(openrouter_key, "OPENROUTER"):
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valid_providers.append("OpenRouter")
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logger.info("OpenRouter API key validated - Multiple models available")
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elif openrouter_key:
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logger.warning("OPENROUTER_API_KEY present but invalid format")
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# Register providers
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if validate_api_key(gemini_key, "GEMINI"):
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ModelProviderRegistry.register_provider(ProviderType.GOOGLE, GeminiModelProvider)
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if validate_api_key(openrouter_key, "OPENROUTER"):
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ModelProviderRegistry.register_provider(ProviderType.OPENROUTER, OpenRouterProvider)
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if not valid_providers:
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error_msg = (
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"No valid API keys found. Please configure at least one:\n"
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" - GEMINI_API_KEY for Google Gemini\n"
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" - OPENROUTER_API_KEY for OpenRouter (minimax, etc.)\n"
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"Create a .env file based on .env.example"
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)
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logger.error(error_msg)
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raise ValueError(error_msg)
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logger.info(f"Configured providers: {', '.join(valid_providers)}")
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logger.info(f"Default model: {DEFAULT_MODEL}")
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# Tool call handlers
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@server.list_tools()
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async def handle_list_tools() -> list[Tool]:
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"""List available tools"""
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tools = []
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for tool_name, tool_instance in TOOLS.items():
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tool_schema = tool_instance.get_input_schema()
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tools.append(
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Tool(
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name=tool_name,
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description=tool_instance.get_description(),
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inputSchema=tool_schema,
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)
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)
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return tools
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@server.call_tool()
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async def handle_call_tool(name: str, arguments: dict) -> list[TextContent]:
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"""Handle tool execution requests"""
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logger.info(f"Tool call: {name}")
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if name not in TOOLS:
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error_msg = f"Unknown tool: {name}"
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logger.error(error_msg)
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return [TextContent(type="text", text=error_msg)]
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try:
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tool = TOOLS[name]
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result: ToolOutput = await tool.execute(arguments)
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if result.is_error:
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logger.error(f"Tool {name} failed: {result.text}")
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else:
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logger.info(f"Tool {name} completed successfully")
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return [TextContent(type="text", text=result.text)]
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except ValueError as e:
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# Validation errors from Pydantic or tool logic
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error_msg = f"Invalid input for {name}: {str(e)}"
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logger.warning(error_msg)
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return [TextContent(type="text", text=error_msg)]
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except ConnectionError as e:
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# Network/API connection issues
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error_msg = f"API connection failed for {name}: {str(e)}\nCheck your API keys and network connection."
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logger.error(error_msg)
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return [TextContent(type="text", text=error_msg)]
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except TimeoutError as e:
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# Request timeout
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error_msg = f"Request timeout for {name}: {str(e)}\nThe AI model took too long to respond. Try again."
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logger.error(error_msg)
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return [TextContent(type="text", text=error_msg)]
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except Exception as e:
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# Unexpected errors
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error_msg = f"Unexpected error in {name}: {str(e)}"
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logger.exception(f"Tool {name} unexpected error: {type(e).__name__}")
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return [TextContent(type="text", text=f"{error_msg}\n\nPlease check the server logs for details.")]
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@server.list_prompts()
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async def handle_list_prompts() -> list[Prompt]:
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"""List available prompt templates"""
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prompts = []
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for tool_name, template_info in PROMPT_TEMPLATES.items():
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if tool_name in TOOLS:
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prompts.append(
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Prompt(
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name=template_info["name"],
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description=template_info["description"],
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arguments=[
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{"name": "model", "description": "AI model to use", "required": False}
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],
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)
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)
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return prompts
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@server.get_prompt()
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async def handle_get_prompt(name: str, arguments: dict | None = None) -> GetPromptResult:
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"""Get a specific prompt template"""
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model = arguments.get("model", DEFAULT_MODEL) if arguments else DEFAULT_MODEL
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for template_info in PROMPT_TEMPLATES.values():
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if template_info["name"] == name:
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prompt_text = template_info["template"].format(model=model)
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return GetPromptResult(
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description=template_info["description"],
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messages=[PromptMessage(role="user", content=TextContent(type="text", text=prompt_text))],
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)
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raise ValueError(f"Unknown prompt: {name}")
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def cleanup():
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"""Cleanup function called on shutdown"""
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logger.info("Zen-Marketing MCP Server shutting down")
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logging.shutdown()
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async def main():
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"""Main entry point"""
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logger.info("=" * 80)
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logger.info(f"Zen-Marketing MCP Server v{__version__}")
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logger.info(f"Python: {sys.version}")
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logger.info(f"Working directory: {os.getcwd()}")
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logger.info("=" * 80)
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# Register cleanup
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atexit.register(cleanup)
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# Configure providers
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try:
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configure_providers()
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except ValueError as e:
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logger.error(f"Configuration error: {e}")
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sys.exit(1)
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# List enabled tools
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logger.info(f"Enabled tools: {sorted(TOOLS.keys())}")
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# Run server
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capabilities = ServerCapabilities(
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tools=ToolsCapability(),
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prompts=PromptsCapability(),
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)
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options = InitializationOptions(
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server_name="zen-marketing",
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server_version=__version__,
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capabilities=capabilities,
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)
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async with stdio_server() as (read_stream, write_stream):
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logger.info("Server started, awaiting requests...")
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await server.run(
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read_stream,
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write_stream,
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options,
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)
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if __name__ == "__main__":
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asyncio.run(main())
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