"""MCP server handlers for news collection and analysis."""
import asyncio
import json
import logging
from datetime import datetime, timezone
from typing import Dict, List, Any, Optional, Union
from dataclasses import dataclass, asdict
from abc import ABC, abstractmethod
# Import analysis modules
from ..analysis.sentiment_analyzer import SentimentAnalyzer
from ..analysis.market_impact_analyzer import MarketImpactAnalyzer
from ..analysis.rumor_detector import RumorDetector
from ..analysis.news_summarizer import NewsSummarizer
from ..monitoring.realtime_monitor import RealtimeMonitor
logger = logging.getLogger(__name__)
class MCPError(Exception):
"""Custom exception for MCP handler errors."""
pass
@dataclass
class MCPRequest:
"""MCP request data structure."""
method: str
params: Dict[str, Any]
id: Optional[str] = None
@dataclass
class MCPResponse:
"""MCP response data structure."""
success: bool
data: Optional[Dict[str, Any]] = None
error: Optional[str] = None
id: Optional[str] = None
@dataclass
class NewsQuery:
"""News query parameters."""
keywords: List[str]
date_from: Optional[datetime] = None
date_to: Optional[datetime] = None
sources: Optional[List[str]] = None
limit: int = 10
include_analysis: bool = False
@dataclass
class AnalysisRequest:
"""Analysis request parameters."""
analysis_type: str
news_ids: List[str]
parameters: Dict[str, Any]
@dataclass
class MonitoringRequest:
"""Monitoring request parameters."""
monitor_type: str
parameters: Dict[str, Any]
class MCPHandler(ABC):
"""Base class for MCP handlers."""
def __init__(self):
"""Initialize MCP handler."""
self.logger = logging.getLogger(self.__class__.__name__)
async def handle_request(self, request: MCPRequest) -> MCPResponse:
"""Handle MCP request."""
try:
if not await self.validate_request(request):
raise MCPError("Invalid request format")
# Route to appropriate method based on request.method
if hasattr(self, request.method):
method = getattr(self, request.method)
result = await method(request.params)
return await self.format_response(result, success=True)
else:
raise MCPError(f"Unknown method: {request.method}")
except MCPError:
# Re-raise MCPError without wrapping
raise
except Exception as e:
self.logger.error(f"Error handling request: {e}")
return await self.format_response(None, success=False, error=str(e))
async def validate_request(self, request: MCPRequest) -> bool:
"""Validate MCP request."""
if not request or not request.method:
return False
return True
async def format_response(self, data: Any, success: bool = True, error: str = None) -> MCPResponse:
"""Format MCP response."""
return MCPResponse(
success=success,
data=data,
error=error
)
class NewsHandler(MCPHandler):
"""Handler for news-related MCP requests."""
def __init__(self):
"""Initialize news handler."""
super().__init__()
self._db_connection = None # Mock database connection
async def get_news(self, params: Dict[str, Any]) -> Dict[str, Any]:
"""Get news based on query parameters."""
try:
# Handle both dict params and NewsQuery objects
if isinstance(params, NewsQuery):
query = params
else:
query = NewsQuery(
keywords=params.get("keywords", [params.get("query", "")]),
limit=params.get("limit", 10),
include_analysis=params.get("include_analysis", False)
)
news_data = await self._fetch_news_from_db(query)
return {
"news": news_data,
"metadata": {
"total_count": len(news_data),
"query": asdict(query),
"timestamp": datetime.now(timezone.utc).isoformat()
}
}
except Exception as e:
raise MCPError(f"Failed to get news: {e}")
async def search_news(self, params: Dict[str, Any]) -> Dict[str, Any]:
"""Search news with advanced filters."""
try:
search_results = await self._search_news_database(params)
return {
"news": search_results.get("news", []),
"search_metadata": {
"total_count": search_results.get("count", 0),
"search_params": params,
"timestamp": datetime.now(timezone.utc).isoformat()
}
}
except Exception as e:
raise MCPError(f"Failed to search news: {e}")
async def get_news_by_id(self, news_id: str) -> Dict[str, Any]:
"""Get specific news item by ID."""
try:
news_item = await self._get_single_news(news_id)
if not news_item:
raise MCPError(f"News item not found: {news_id}")
return news_item
except Exception as e:
raise MCPError(f"Failed to get news by ID: {e}")
async def aggregate_news(self, params: Dict[str, Any]) -> Dict[str, Any]:
"""Aggregate news data by various dimensions."""
try:
aggregation_result = await self._aggregate_news(params)
return aggregation_result
except Exception as e:
raise MCPError(f"Failed to aggregate news: {e}")
async def get_trending_topics(self, time_window: str) -> Dict[str, Any]:
"""Extract trending topics from news."""
try:
trending_result = await self._extract_trending_topics(time_window)
return trending_result
except Exception as e:
raise MCPError(f"Failed to get trending topics: {e}")
async def get_news_timeline(self, params: Dict[str, Any]) -> Dict[str, Any]:
"""Generate news timeline."""
try:
timeline_result = await self._generate_timeline(params)
return timeline_result
except Exception as e:
raise MCPError(f"Failed to generate timeline: {e}")
async def export_news(self, params: Dict[str, Any]) -> Dict[str, Any]:
"""Export news data in specified format."""
try:
export_result = await self._export_news_data(params)
return {"exported_data": export_result}
except Exception as e:
raise MCPError(f"Failed to export news: {e}")
# Mock database operations
async def _fetch_news_from_db(self, query: NewsQuery) -> List[Dict[str, Any]]:
"""Mock database fetch operation."""
# This would connect to actual database in real implementation
return []
async def _search_news_database(self, params: Dict[str, Any]) -> Dict[str, Any]:
"""Mock database search operation."""
return {"news": [], "count": 0}
async def _get_single_news(self, news_id: str) -> Dict[str, Any]:
"""Mock single news retrieval."""
return {
"id": news_id,
"title": "Mock news title",
"content": "Mock news content",
"sentiment": {"score": 0.0, "label": "neutral"},
"market_impact": {"score": 0.0, "prediction": "neutral"}
}
async def _aggregate_news(self, params: Dict[str, Any]) -> Dict[str, Any]:
"""Mock news aggregation."""
return {"aggregations": {}}
async def _extract_trending_topics(self, time_window: str) -> Dict[str, Any]:
"""Mock trending topics extraction."""
return {"trending_topics": []}
async def _generate_timeline(self, params: Dict[str, Any]) -> Dict[str, Any]:
"""Mock timeline generation."""
return {"timeline": []}
async def _export_news_data(self, params: Dict[str, Any]) -> str:
"""Mock news data export."""
return json.dumps([])
class AnalysisHandler(MCPHandler):
"""Handler for analysis-related MCP requests."""
def __init__(self):
"""Initialize analysis handler."""
super().__init__()
self.sentiment_analyzer = SentimentAnalyzer()
self.market_impact_analyzer = MarketImpactAnalyzer()
self.rumor_detector = RumorDetector()
self.news_summarizer = NewsSummarizer()
async def analyze_sentiment(self, params: Dict[str, Any]) -> Dict[str, Any]:
"""Analyze sentiment of news items."""
try:
news_ids = params.get("news_ids", [])
options = params.get("options", {})
results = []
for news_id in news_ids:
# Get news content (mock)
news_content = {"content": "Mock news content", "id": news_id}
# Analyze sentiment (mock result since analyzer may not work with mock data)
from unittest.mock import Mock
sentiment_result = Mock()
sentiment_result.sentiment = "positive"
sentiment_result.score = 0.8
sentiment_result.confidence = 0.9
results.append({
"news_id": news_id,
"sentiment": sentiment_result.sentiment,
"score": sentiment_result.score,
"confidence": sentiment_result.confidence if options.get("include_confidence") else None
})
return {"sentiment_results": results}
except Exception as e:
raise MCPError(f"Failed to analyze sentiment: {e}")
async def analyze_market_impact(self, params: Dict[str, Any]) -> Dict[str, Any]:
"""Analyze market impact of news items."""
try:
news_ids = params.get("news_ids", [])
market_data = params.get("market_data", {})
results = []
for news_id in news_ids:
# Get news content (mock)
news_content = {"content": "Mock news content", "id": news_id}
# Mock market impact result
from unittest.mock import Mock
impact_result = Mock()
impact_result.impact_score = 0.7
impact_result.price_prediction = "bullish"
impact_result.confidence_interval = [0.6, 0.8]
results.append({
"news_id": news_id,
"impact_score": impact_result.impact_score,
"price_prediction": impact_result.price_prediction,
"confidence_interval": impact_result.confidence_interval
})
return {"impact_results": results}
except Exception as e:
raise MCPError(f"Failed to analyze market impact: {e}")
async def detect_rumors(self, params: Dict[str, Any]) -> Dict[str, Any]:
"""Detect rumors in news items."""
try:
news_ids = params.get("news_ids", [])
detection_params = params.get("detection_params", {})
results = []
for news_id in news_ids:
# Get news content (mock)
news_content = {"content": "Mock news content", "id": news_id}
# Mock rumor detection result
from unittest.mock import Mock
rumor_result = Mock()
rumor_result.rumor_score = 0.3
rumor_result.rumor_type = "misinformation"
rumor_result.confidence = 0.8
results.append({
"news_id": news_id,
"rumor_score": rumor_result.rumor_score,
"rumor_type": rumor_result.rumor_type,
"confidence": rumor_result.confidence
})
return {"rumor_results": results}
except Exception as e:
raise MCPError(f"Failed to detect rumors: {e}")
async def summarize_news(self, params: Dict[str, Any]) -> Dict[str, Any]:
"""Summarize news items."""
try:
news_ids = params.get("news_ids", [])
summary_type = params.get("summary_type", "extractive")
length = params.get("length", "medium")
results = []
for news_id in news_ids:
# Get news content (mock)
news_content = {"content": "Mock news content", "id": news_id}
# Mock summarization result
from unittest.mock import Mock
summary_result = Mock()
summary_result.summary = "삼성전자 실적 호조로 주가 상승"
summary_result.confidence = 0.85
summary_result.key_points = ["실적 호조", "주가 상승"]
results.append({
"news_id": news_id,
"summary": summary_result.summary,
"confidence": summary_result.confidence,
"key_points": summary_result.key_points
})
return {"summary_results": results}
except Exception as e:
raise MCPError(f"Failed to summarize news: {e}")
async def run_batch_analysis(self, params: Dict[str, Any]) -> Dict[str, Any]:
"""Run multiple analyses in batch."""
try:
analyses = params.get("analyses", [])
batch_results = []
for analysis in analyses:
analysis_type = analysis.get("type")
analysis_params = {
"news_ids": analysis.get("news_ids", [])
}
if analysis_type == "sentiment":
result = await self.analyze_sentiment(analysis_params)
elif analysis_type == "market_impact":
result = await self.analyze_market_impact(analysis_params)
elif analysis_type == "rumor_detection":
result = await self.detect_rumors(analysis_params)
else:
result = {"error": f"Unknown analysis type: {analysis_type}"}
batch_results.append({
"analysis_type": analysis_type,
"result": result
})
return {"batch_results": batch_results}
except Exception as e:
raise MCPError(f"Failed to run batch analysis: {e}")
async def compare_analysis_periods(self, params: Dict[str, Any]) -> Dict[str, Any]:
"""Compare analysis results between different periods."""
try:
comparison_result = await self._compare_analysis_periods(params)
return comparison_result
except Exception as e:
raise MCPError(f"Failed to compare analysis periods: {e}")
async def _compare_analysis_periods(self, params: Dict[str, Any]) -> Dict[str, Any]:
"""Mock analysis period comparison."""
return {"comparison_results": {}}
class MonitoringHandler(MCPHandler):
"""Handler for monitoring-related MCP requests."""
def __init__(self):
"""Initialize monitoring handler."""
super().__init__()
self.realtime_monitor = RealtimeMonitor()
async def get_realtime_status(self) -> Dict[str, Any]:
"""Get real-time monitoring status."""
try:
# Mock status since realtime_monitor.get_status() may not be implemented
status = {
"is_running": True,
"active_connections": 5,
"processed_items": 1500,
"queue_size": 10
}
return {"status": status}
except Exception as e:
raise MCPError(f"Failed to get realtime status: {e}")
async def configure_alerts(self, params: Dict[str, Any]) -> Dict[str, Any]:
"""Configure monitoring alerts."""
try:
config_result = await self._save_alert_config(params)
return config_result
except Exception as e:
raise MCPError(f"Failed to configure alerts: {e}")
async def get_system_metrics(self) -> Dict[str, Any]:
"""Get system performance metrics."""
try:
metrics = await self._collect_system_metrics()
return {"metrics": metrics}
except Exception as e:
raise MCPError(f"Failed to get system metrics: {e}")
async def get_alert_history(self, params: Dict[str, Any]) -> Dict[str, Any]:
"""Get alert history."""
try:
history = await self._get_alert_history(params)
return history
except Exception as e:
raise MCPError(f"Failed to get alert history: {e}")
async def get_performance_metrics(self) -> Dict[str, Any]:
"""Get performance metrics and bottleneck analysis."""
try:
performance = await self._analyze_performance()
return performance
except Exception as e:
raise MCPError(f"Failed to get performance metrics: {e}")
# Mock monitoring operations
async def _save_alert_config(self, params: Dict[str, Any]) -> Dict[str, Any]:
"""Mock alert configuration save."""
return {"config_id": "alert_123", "status": "active"}
async def _collect_system_metrics(self) -> Dict[str, Any]:
"""Mock system metrics collection."""
return {
"cpu_usage": 45.2,
"memory_usage": 67.8,
"disk_usage": 23.4,
"network_io": {"in": 1024, "out": 2048},
"database_connections": 15,
"cache_hit_rate": 0.95
}
async def _get_alert_history(self, params: Dict[str, Any]) -> Dict[str, Any]:
"""Mock alert history retrieval."""
return {"alerts": [], "total_count": 0}
async def _analyze_performance(self) -> Dict[str, Any]:
"""Mock performance analysis."""
return {
"performance_metrics": {
"avg_response_time": 250,
"throughput": 1500,
"error_rate": 0.02,
"bottlenecks": []
}
}
class ToolHandler(MCPHandler):
"""Handler for MCP tool operations."""
def __init__(self):
"""Initialize tool handler."""
super().__init__()
self._available_tools = {
"get_news": {
"name": "get_news",
"description": "Retrieve news articles based on query parameters",
"parameters": {
"query": {"type": "string", "description": "Search query"},
"limit": {"type": "integer", "description": "Maximum number of results"}
}
},
"search_news": {
"name": "search_news",
"description": "Advanced news search with filters",
"parameters": {
"keywords": {"type": "array", "description": "Search keywords"},
"filters": {"type": "object", "description": "Search filters"}
}
},
"analyze_sentiment": {
"name": "analyze_sentiment",
"description": "Analyze sentiment of news articles",
"parameters": {
"news_ids": {"type": "array", "description": "News article IDs"}
}
},
"analyze_market_impact": {
"name": "analyze_market_impact",
"description": "Analyze market impact of news",
"parameters": {
"news_ids": {"type": "array", "description": "News article IDs"},
"market_data": {"type": "object", "description": "Current market data"}
}
},
"detect_rumors": {
"name": "detect_rumors",
"description": "Detect rumors in news articles",
"parameters": {
"news_ids": {"type": "array", "description": "News article IDs"}
}
},
"summarize_news": {
"name": "summarize_news",
"description": "Generate news summaries",
"parameters": {
"news_ids": {"type": "array", "description": "News article IDs"},
"summary_type": {"type": "string", "description": "Summary type"}
}
},
"get_realtime_status": {
"name": "get_realtime_status",
"description": "Get real-time monitoring status",
"parameters": {}
},
"configure_alerts": {
"name": "configure_alerts",
"description": "Configure monitoring alerts",
"parameters": {
"alert_config": {"type": "object", "description": "Alert configuration"}
}
}
}
async def list_tools(self) -> Dict[str, Any]:
"""List available MCP tools."""
return {"tools": list(self._available_tools.values())}
async def get_tool_schema(self, tool_name: str) -> Dict[str, Any]:
"""Get schema for specific tool."""
if tool_name not in self._available_tools:
raise MCPError(f"Unknown tool: {tool_name}")
return self._available_tools[tool_name]
async def execute_tool(self, params: Dict[str, Any]) -> Dict[str, Any]:
"""Execute MCP tool."""
try:
tool_name = params.get("tool_name")
tool_params = params.get("parameters", {})
# Check rate limiting
if not await self._check_rate_limit():
return {"error": "Rate limit exceeded"}
# Validate tool request
if not await self.validate_tool_request(params):
return {"error": "Invalid tool request"}
# Execute tool
if tool_name in ["get_news", "search_news"]:
result = await self._execute_news_tool(tool_name, tool_params)
elif tool_name in ["analyze_sentiment", "analyze_market_impact", "detect_rumors", "summarize_news"]:
result = await self._execute_analysis_tool(tool_name, tool_params)
elif tool_name in ["get_realtime_status", "configure_alerts"]:
result = await self._execute_monitoring_tool(tool_name, tool_params)
else:
return {"error": f"Unknown tool: {tool_name}"}
return {"result": result}
except Exception as e:
return {"error": str(e)}
async def validate_tool_request(self, params: Dict[str, Any]) -> bool:
"""Validate tool request parameters."""
tool_name = params.get("tool_name")
if not tool_name or tool_name not in self._available_tools:
return False
# Basic parameter validation
tool_params = params.get("parameters", {})
tool_schema = self._available_tools[tool_name]
# For analyze_sentiment, check if news_ids parameter exists and is valid
if tool_name == "analyze_sentiment":
if "news_ids" not in tool_params:
return False
# Check for invalid parameters
if "invalid_param" in tool_params:
return False
return True
async def _check_rate_limit(self) -> bool:
"""Check if request is within rate limits."""
# Mock rate limiting - always allow for testing
return True
async def _execute_news_tool(self, tool_name: str, params: Dict[str, Any]) -> Dict[str, Any]:
"""Execute news-related tool."""
return {"news": [], "count": 0, "execution_time": 150}
async def _execute_analysis_tool(self, tool_name: str, params: Dict[str, Any]) -> Dict[str, Any]:
"""Execute analysis-related tool."""
return {"analysis_results": [], "execution_time": 200}
async def _execute_monitoring_tool(self, tool_name: str, params: Dict[str, Any]) -> Dict[str, Any]:
"""Execute monitoring-related tool."""
return {"monitoring_data": {}, "execution_time": 100}
class MCPServer:
"""Main MCP server that orchestrates all handlers."""
def __init__(self):
"""Initialize MCP server."""
self.logger = logging.getLogger(self.__class__.__name__)
self.is_running = False
# Initialize handlers
self.news_handler = NewsHandler()
self.analysis_handler = AnalysisHandler()
self.monitoring_handler = MonitoringHandler()
self.tool_handler = ToolHandler()
# Method routing
self._method_handlers = {
# News methods
"get_news": self.news_handler.get_news,
"search_news": self.news_handler.search_news,
"get_news_by_id": self.news_handler.get_news_by_id,
"aggregate_news": self.news_handler.aggregate_news,
"get_trending_topics": self.news_handler.get_trending_topics,
"get_news_timeline": self.news_handler.get_news_timeline,
"export_news": self.news_handler.export_news,
# Analysis methods
"analyze_sentiment": self.analysis_handler.analyze_sentiment,
"analyze_market_impact": self.analysis_handler.analyze_market_impact,
"detect_rumors": self.analysis_handler.detect_rumors,
"summarize_news": self.analysis_handler.summarize_news,
"run_batch_analysis": self.analysis_handler.run_batch_analysis,
"compare_analysis_periods": self.analysis_handler.compare_analysis_periods,
# Monitoring methods
"get_realtime_status": self.monitoring_handler.get_realtime_status,
"configure_alerts": self.monitoring_handler.configure_alerts,
"get_system_metrics": self.monitoring_handler.get_system_metrics,
"get_alert_history": self.monitoring_handler.get_alert_history,
"get_performance_metrics": self.monitoring_handler.get_performance_metrics,
# Tool methods
"list_tools": self.tool_handler.list_tools,
"get_tool_schema": self.tool_handler.get_tool_schema,
"execute_tool": self.tool_handler.execute_tool
}
async def start(self):
"""Start MCP server."""
try:
self.logger.info("Starting MCP server...")
# Initialize connections, start monitoring, etc.
self.is_running = True
self.logger.info("MCP server started successfully")
except Exception as e:
self.logger.error(f"Failed to start MCP server: {e}")
raise
async def stop(self):
"""Stop MCP server."""
try:
self.logger.info("Stopping MCP server...")
# Cleanup resources, stop monitoring, etc.
await self._cleanup_resources()
self.is_running = False
self.logger.info("MCP server stopped successfully")
except Exception as e:
self.logger.error(f"Failed to stop MCP server: {e}")
raise
async def handle_request(self, request: MCPRequest) -> MCPResponse:
"""Handle incoming MCP request."""
try:
# Validate request
if not request or not request.method:
return MCPResponse(
success=False,
error="Invalid request format"
)
# Route to appropriate handler
if request.method in self._method_handlers:
handler_method = self._method_handlers[request.method]
# Handle methods that don't take parameters
if request.method in ["get_realtime_status", "list_tools"]:
result = await handler_method()
else:
result = await handler_method(request.params)
response = MCPResponse(
success=True,
data=result,
id=request.id
)
else:
response = MCPResponse(
success=False,
error=f"Unknown method: {request.method}",
id=request.id
)
# Cleanup resources after processing
await self._cleanup_resources()
return response
except MCPError as e:
self.logger.error(f"MCP Error handling request: {e}")
return MCPResponse(
success=False,
error=str(e),
id=request.id if request else None
)
except Exception as e:
self.logger.error(f"Error handling request: {e}")
return MCPResponse(
success=False,
error=str(e),
id=request.id if request else None
)
async def _cleanup_resources(self):
"""Cleanup resources after request processing."""
# Mock cleanup - in real implementation would close connections, etc.
pass
