refactor: MCP 공통 함수/httpx 싱글톤, CORS 수정, ML 이벤트루프 블로킹 해소 (#4~#7)

mcp-server/config.py

@@ -45,5 +45,14 @@ class Settings:
     CHART_DAYS = int(os.getenv("CHART_DAYS", "100"))
     JSON_COMPACT = os.getenv("JSON_COMPACT", "false").lower() == "true"
 
+    # CORS (이슈 5)
+    # 서버-서버 통신용: 브라우저 credentials 불필요.
+    # Docker 환경: MCP_CORS_ORIGINS=http://backend:8000
+    # 개발 환경:   MCP_CORS_ORIGINS=http://localhost:8000,http://127.0.0.1:8000
+    MCP_CORS_ORIGINS = os.getenv(
+        "MCP_CORS_ORIGINS",
+        "http://localhost:8000,http://127.0.0.1:8000,http://backend:8000",
+    )
+
 
 settings = Settings()

mcp-server/main.py

@@ -29,13 +29,22 @@ app = FastAPI(
     version="1.0.0"
 )
 
-# CORS 설정
+# CORS 설정 (이슈 5)
+# 문제: allow_origins=["*"] + allow_credentials=True 조합은 CORS 스펙 위반 (브라우저 차단)
+# 해결: 환경변수 MCP_CORS_ORIGINS로 origin 제한 + allow_credentials=False (서버-서버 통신 불필요)
+_raw_cors = settings.MCP_CORS_ORIGINS
+_allowed_origins = (
+    [o.strip() for o in _raw_cors.split(",") if o.strip()]
+    if _raw_cors
+    else ["http://localhost:8000", "http://127.0.0.1:8000", "http://backend:8000"]
+)
+logger.info(f"MCP CORS allowed origins: {_allowed_origins}")
 app.add_middleware(
     CORSMiddleware,
-    allow_origins=["*"],
-    allow_credentials=True,
-    allow_methods=["*"],
-    allow_headers=["*"],
+    allow_origins=_allowed_origins,
+    allow_credentials=False,   # 서버-서버 통신; 브라우저 세션 쿠키 불필요
+    allow_methods=["GET", "POST"],
+    allow_headers=["Content-Type", "Authorization"],
 )
 
 
@@ -93,19 +102,15 @@ async def analyze(request: AnalysisRequest):
     try:
         analysis_type = request.analysis_type
         data = request.data
-        
+
         if analysis_type == "RULE_VALIDATION":
-            # 규칙 검증
             rule = data.get("rule")
             market_data = data.get("market_data")
-            
             if not rule or not market_data:
                 raise HTTPException(
                     status_code=400,
                     detail="rule and market_data are required"
                 )
-            
-            # 뉴스 정보 추가 수집
             stock_code = market_data.get("stock_code")
             news_data = []
             if stock_code:
@@ -115,80 +120,56 @@ async def analyze(request: AnalysisRequest):
                         news_data = news_result["news"]
                 except Exception as e:
                     logger.warning(f"Failed to fetch news for validation: {e}")
-
             result = await ai_client.validate_trading_rule(rule, market_data, news_data)
-            return {
-                "analysis_type": analysis_type,
-                "result": result
-            }
-        
+            return {"analysis_type": analysis_type, "result": result}
+
         elif analysis_type == "MARKET_ANALYSIS":
-            # 시장 분석
             stock_code = data.get("stock_code")
             market_data = data.get("market_data")
             news = data.get("news", [])
-            
             if not stock_code or not market_data:
                 raise HTTPException(
                     status_code=400,
                     detail="stock_code and market_data are required"
                 )
-            
             result = await ai_client.analyze_market(stock_code, market_data, news)
-            return {
-                "analysis_type": analysis_type,
-                "result": result
-            }
-        
+            return {"analysis_type": analysis_type, "result": result}
+
         elif analysis_type == "RISK_ASSESSMENT":
-            # 리스크 평가
-            portfolio = data.get("portfolio")
+            # 이슈 4: request_mcp_risk_assessment()가 trade_plan/portfolio/signals 전달
+            portfolio = data.get("portfolio") or {}
             trade_plan = data.get("trade_plan")
-            
-            if not portfolio or not trade_plan:
+            signals = data.get("signals") or {}
+            if not trade_plan:
                 raise HTTPException(
                     status_code=400,
-                    detail="portfolio and trade_plan are required"
+                    detail="trade_plan is required"
                 )
-            
             result = await ai_client.assess_risk(portfolio, trade_plan)
-            return {
-                "analysis_type": analysis_type,
-                "result": result
-            }
-        
+            return {"analysis_type": analysis_type, "result": result}
+
         elif analysis_type == "FAIR_PRICE":
-            # 적정가 분석
             stock_code = data.get("stock_code")
             market_data = data.get("market_data")
             financial_data = data.get("financial_data")
-            
             if not stock_code or not market_data:
                 raise HTTPException(
                     status_code=400,
                     detail="stock_code and market_data are required"
                 )
-            
             result = await ai_client.calculate_fair_price(
                 stock_code, market_data, financial_data
             )
-            return {
-                "analysis_type": analysis_type,
-                "result": result
-            }
-            
+            return {"analysis_type": analysis_type, "result": result}
+
         elif analysis_type == "RULE_OPTIMIZATION":
-            # 트레이딩 규칙 최적화/생성
             stock_code = data.get("stock_code")
             market_data = data.get("market_data")
-            
             if not stock_code or not market_data:
                 raise HTTPException(
                     status_code=400,
                     detail="stock_code and market_data are required"
                 )
-            
-            # 뉴스 정보 추가 수집
             news_data = []
             try:
                 news_result = await mcp_tools.get_news(stock_code, limit=settings.NEWS_LIMIT)
@@ -196,36 +177,26 @@ async def analyze(request: AnalysisRequest):
                     news_data = news_result["news"]
             except Exception as e:
                 logger.warning(f"Failed to fetch news for optimization: {e}")
-                
             result = await ai_client.optimize_trading_rules(stock_code, market_data, news_data)
-            return {
-                "analysis_type": analysis_type,
-                "result": result
-            }
-            
+            return {"analysis_type": analysis_type, "result": result}
+
         elif analysis_type == "GENERATE_JOURNAL":
-            # 매매일지 생성
             trade_info = data.get("trade_info")
             market_data = data.get("market_data")
-            
             if not trade_info or not market_data:
                 raise HTTPException(
                     status_code=400,
                     detail="trade_info and market_data are required"
                 )
-                
             result = await ai_client.generate_trade_journal(trade_info, market_data)
-            return {
-                "analysis_type": analysis_type,
-                "result": result
-            }
-        
+            return {"analysis_type": analysis_type, "result": result}
+
         else:
             raise HTTPException(
                 status_code=400,
                 detail=f"Unknown analysis type: {analysis_type}"
             )
-    
+
     except HTTPException:
         raise
     except Exception as e: