fix: use 'args' instead of 'arguments' in MCPToolCallRequest

MCPToolCallRequest has 'args' attribute, not 'arguments'. Fixed
attribute name to match the actual API.

.env.example

@@ -35,7 +35,7 @@ MAX_SIMULATION_DAYS=30
 AUTO_DOWNLOAD_PRICE_DATA=true
 
 # Data Volume Configuration
-# Base directory for all persistent data (will contain data/, logs/, configs/ subdirectories)
+# Base directory for all persistent data (will contain data/ and configs/ subdirectories)
 # Use relative paths (./volumes) or absolute paths (/home/user/ai-trader-volumes)
 # Defaults to current directory (.) if not set
 VOLUME_PATH=.

DOCKER.md

@@ -154,10 +154,9 @@ docker-compose up
 
 ### Volume Mounts
 
-Docker Compose mounts three volumes for persistent data. By default, these are stored in the project directory:
+Docker Compose mounts two volumes for persistent data. By default, these are stored in the project directory:
 
 - `./data:/app/data` - Price data and trading records
-- `./logs:/app/logs` - MCP service logs
 - `./configs:/app/configs` - Configuration files (allows editing configs without rebuilding)
 
 ### Custom Volume Location
@@ -174,7 +173,6 @@ VOLUME_PATH=./volumes
 
 This will store data in:
 - `/home/user/trading-data/data/`
-- `/home/user/trading-data/logs/`
 - `/home/user/trading-data/configs/`
 
 **Note:** The directory structure is automatically created. You'll need to copy your existing configs:
@@ -190,7 +188,7 @@ To reset all trading data:
 
 ```bash
 docker-compose down
-rm -rf ${VOLUME_PATH:-.}/data/agent_data/* ${VOLUME_PATH:-.}/logs/*
+rm -rf ${VOLUME_PATH:-.}/data/agent_data/*
 docker-compose up
 ```
 
@@ -217,8 +215,7 @@ docker pull ghcr.io/xe138/ai-trader-server:latest
 ```bash
 docker run --env-file .env \
   -v $(pwd)/data:/app/data \
-  -v $(pwd)/logs:/app/logs \
-  -p 8000-8003:8000-8003 \
+  -p 8080:8080 \
   ghcr.io/xe138/ai-trader-server:latest
 ```
 
@@ -234,9 +231,9 @@ docker pull ghcr.io/xe138/ai-trader-server:v1.0.0
 **Symptom:** Container exits immediately or errors about ports
 
 **Solutions:**
-- Check ports 8000-8003 not already in use: `lsof -i :8000-8003`
 - View container logs: `docker-compose logs`
-- Check MCP service logs: `cat logs/math.log`
+- Check if API port 8080 is already in use: `lsof -i :8080`
+- Verify MCP services started by checking Docker logs for service startup messages
 
 ### Missing API Keys
 
@@ -258,12 +255,12 @@ docker pull ghcr.io/xe138/ai-trader-server:v1.0.0
 
 ### Permission Issues
 
-**Symptom:** Cannot write to data or logs directories
+**Symptom:** Cannot write to data directory
 
 **Solutions:**
-- Ensure directories writable: `chmod -R 755 data logs`
+- Ensure data directory is writable: `chmod -R 755 data`
 - Check volume mount permissions
-- May need to create directories first: `mkdir -p data logs`
+- May need to create directory first: `mkdir -p data`
 
 ### Container Keeps Restarting
 
@@ -298,13 +295,12 @@ docker buildx build --platform linux/amd64,linux/arm64 -t ai-trader-server .
 docker stats ai-trader-server
 ```
 
-### Access MCP Services Directly
+### Access API Directly
 
-Services exposed on host:
-- Math: http://localhost:8000
-- Search: http://localhost:8001
-- Trade: http://localhost:8002
-- Price: http://localhost:8003
+API server exposed on host:
+- REST API: http://localhost:8080
+
+MCP services run internally and are not exposed to the host.
 
 ## Development Workflow
 

Dockerfile

@@ -26,14 +26,8 @@ WORKDIR /app
 # Copy application code
 COPY . .
 
-# Copy data scripts to separate directory (volume mount won't overlay these)
-RUN mkdir -p /app/scripts && \
-    cp data/get_daily_price.py /app/scripts/ && \
-    cp data/get_interdaily_price.py /app/scripts/ && \
-    cp data/merge_jsonl.py /app/scripts/
-
 # Create necessary directories
-RUN mkdir -p data logs data/agent_data
+RUN mkdir -p data data/agent_data
 
 # Make entrypoint executable
 RUN chmod +x entrypoint.sh

agent/base_agent/base_agent.py

@@ -29,6 +29,7 @@ from tools.deployment_config import (
     log_api_key_warning,
     get_deployment_mode
 )
+from agent.context_injector import ContextInjector
 
 # Load environment variables
 load_dotenv()
@@ -124,6 +125,9 @@ class BaseAgent:
         self.tools: Optional[List] = None
         self.model: Optional[ChatOpenAI] = None
         self.agent: Optional[Any] = None
+
+        # Context injector for MCP tools
+        self.context_injector: Optional[ContextInjector] = None
         
         # Data paths
         self.data_path = os.path.join(self.base_log_path, self.signature)
@@ -169,16 +173,27 @@ class BaseAgent:
                 print("⚠️  OpenAI base URL not set, using default")
 
         try:
-            # Create MCP client
-            self.client = MultiServerMCPClient(self.mcp_config)
+            # Create context injector for injecting signature and today_date into tool calls
+            self.context_injector = ContextInjector(
+                signature=self.signature,
+                today_date=self.init_date  # Will be updated per trading session
+            )
+
+            # Create MCP client with interceptor
+            self.client = MultiServerMCPClient(
+                self.mcp_config,
+                tool_interceptors=[self.context_injector]
+            )
 
             # Get tools
-            self.tools = await self.client.get_tools()
-            if not self.tools:
+            raw_tools = await self.client.get_tools()
+            if not raw_tools:
                 print("⚠️  Warning: No MCP tools loaded. MCP services may not be running.")
                 print(f"   MCP configuration: {self.mcp_config}")
+                self.tools = []
             else:
-                print(f"✅ Loaded {len(self.tools)} MCP tools")
+                print(f"✅ Loaded {len(raw_tools)} MCP tools")
+                self.tools = raw_tools
         except Exception as e:
             raise RuntimeError(
                 f"❌ Failed to initialize MCP client: {e}\n"
@@ -336,6 +351,10 @@ Summary:"""
         """
         print(f"📈 Starting trading session: {today_date}")
 
+        # Update context injector with current trading date
+        if self.context_injector:
+            self.context_injector.today_date = today_date
+
         # Clear conversation history for new trading day
         self.clear_conversation_history()
 

agent/context_injector.py

@@ -0,0 +1,55 @@
+"""
+Tool interceptor for injecting runtime context into MCP tool calls.
+
+This interceptor automatically injects `signature` and `today_date` parameters
+into buy/sell tool calls to support concurrent multi-model simulations.
+"""
+
+from typing import Any, Callable, Awaitable
+
+
+class ContextInjector:
+    """
+    Intercepts tool calls to inject runtime context (signature, today_date).
+
+    Usage:
+        interceptor = ContextInjector(signature="gpt-5", today_date="2025-10-01")
+        client = MultiServerMCPClient(config, tool_interceptors=[interceptor])
+    """
+
+    def __init__(self, signature: str, today_date: str):
+        """
+        Initialize context injector.
+
+        Args:
+            signature: Model signature to inject
+            today_date: Trading date to inject
+        """
+        self.signature = signature
+        self.today_date = today_date
+
+    async def __call__(
+        self,
+        request: Any,  # MCPToolCallRequest
+        handler: Callable[[Any], Awaitable[Any]]
+    ) -> Any:  # MCPToolCallResult
+        """
+        Intercept tool call and inject context parameters.
+
+        Args:
+            request: Tool call request containing name and arguments
+            handler: Async callable to execute the actual tool
+
+        Returns:
+            Result from handler after injecting context
+        """
+        # Inject signature and today_date for trade tools
+        if request.name in ["buy", "sell"]:
+            # Add signature and today_date to args if not present
+            if "signature" not in request.args:
+                request.args["signature"] = self.signature
+            if "today_date" not in request.args:
+                request.args["today_date"] = self.today_date
+
+        # Call the actual tool handler
+        return await handler(request)

agent_tools/start_mcp_services.py

@@ -52,10 +52,6 @@ class MCPServiceManager:
             }
         }
 
-        # Create logs directory
-        self.log_dir = Path('logs')
-        self.log_dir.mkdir(exist_ok=True)
-        
         # Set signal handlers
         signal.signal(signal.SIGINT, self.signal_handler)
         signal.signal(signal.SIGTERM, self.signal_handler)
@@ -77,27 +73,23 @@ class MCPServiceManager:
             return False
 
         try:
-            # Start service process
-            log_file = self.log_dir / f"{service_id}.log"
-
             # Set PYTHONPATH to /app so services can import from tools module
             env = os.environ.copy()
             env['PYTHONPATH'] = str(Path.cwd())
 
-            with open(log_file, 'w') as f:
-                process = subprocess.Popen(
-                    [sys.executable, str(script_path)],
-                    stdout=f,
-                    stderr=subprocess.STDOUT,
-                    cwd=Path.cwd(),  # Use current working directory (/app)
-                    env=env  # Pass environment with PYTHONPATH
-                )
-            
+            # Start service process (output goes to Docker logs)
+            process = subprocess.Popen(
+                [sys.executable, str(script_path)],
+                stdout=subprocess.DEVNULL,
+                stderr=subprocess.DEVNULL,
+                cwd=Path.cwd(),  # Use current working directory (/app)
+                env=env  # Pass environment with PYTHONPATH
+            )
+
             self.services[service_id] = {
                 'process': process,
                 'name': service_name,
-                'port': port,
-                'log_file': log_file
+                'port': port
             }
             
             print(f"✅ {service_name} service started (PID: {process.pid}, Port: {port})")
@@ -167,15 +159,14 @@ class MCPServiceManager:
                 print(f"✅ {service['name']} service running normally")
             else:
                 print(f"❌ {service['name']} service failed to start")
-                print(f"   Please check logs: {service['log_file']}")
+                print(f"   Check Docker logs for details: docker logs ai-trader-server")
     
     def print_service_info(self):
         """Print service information"""
         print("\n📋 Service information:")
         for service_id, service in self.services.items():
             print(f"  - {service['name']}: http://localhost:{service['port']} (PID: {service['process'].pid})")
-        
-        print(f"\n📁 Log files location: {self.log_dir.absolute()}")
+
         print("\n🛑 Press Ctrl+C to stop all services")
     
     def keep_alive(self):

agent_tools/tool_trade.py

@@ -13,41 +13,45 @@ mcp = FastMCP("TradeTools")
 
 
 @mcp.tool()
-def buy(symbol: str, amount: int) -> Dict[str, Any]:
+def buy(symbol: str, amount: int, signature: str = None, today_date: str = None) -> Dict[str, Any]:
     """
     Buy stock function
-    
+
     This function simulates stock buying operations, including the following steps:
     1. Get current position and operation ID
     2. Get stock opening price for the day
     3. Validate buy conditions (sufficient cash)
     4. Update position (increase stock quantity, decrease cash)
     5. Record transaction to position.jsonl file
-    
+
     Args:
         symbol: Stock symbol, such as "AAPL", "MSFT", etc.
         amount: Buy quantity, must be a positive integer, indicating how many shares to buy
-        
+        signature: Model signature (optional, will use config/env if not provided)
+        today_date: Trading date (optional, will use config/env if not provided)
+
     Returns:
         Dict[str, Any]:
           - Success: Returns new position dictionary (containing stock quantity and cash balance)
           - Failure: Returns {"error": error message, ...} dictionary
-        
+
     Raises:
         ValueError: Raised when SIGNATURE environment variable is not set
-        
+
     Example:
         >>> result = buy("AAPL", 10)
         >>> print(result)  # {"AAPL": 110, "MSFT": 5, "CASH": 5000.0, ...}
     """
     # Step 1: Get environment variables and basic information
-    # Get signature (model name) from environment variable, used to determine data storage path
-    signature = get_config_value("SIGNATURE")
+    # Get signature (model name) from parameter or fallback to config/env
     if signature is None:
-        raise ValueError("SIGNATURE environment variable is not set")
-    
-    # Get current trading date from environment variable
-    today_date = get_config_value("TODAY_DATE")
+        signature = get_config_value("SIGNATURE")
+    if signature is None:
+        raise ValueError("SIGNATURE not provided and environment variable is not set")
+
+    # Get current trading date from parameter or fallback to config/env
+    if today_date is None:
+        today_date = get_config_value("TODAY_DATE")
     
     # Step 2: Get current latest position and operation ID
     # get_latest_position returns two values: position dictionary and current maximum operation ID
@@ -104,41 +108,45 @@ def buy(symbol: str, amount: int) -> Dict[str, Any]:
         return new_position
 
 @mcp.tool()
-def sell(symbol: str, amount: int) -> Dict[str, Any]:
+def sell(symbol: str, amount: int, signature: str = None, today_date: str = None) -> Dict[str, Any]:
     """
     Sell stock function
-    
+
     This function simulates stock selling operations, including the following steps:
     1. Get current position and operation ID
     2. Get stock opening price for the day
     3. Validate sell conditions (position exists, sufficient quantity)
     4. Update position (decrease stock quantity, increase cash)
     5. Record transaction to position.jsonl file
-    
+
     Args:
         symbol: Stock symbol, such as "AAPL", "MSFT", etc.
         amount: Sell quantity, must be a positive integer, indicating how many shares to sell
-        
+        signature: Model signature (optional, will use config/env if not provided)
+        today_date: Trading date (optional, will use config/env if not provided)
+
     Returns:
         Dict[str, Any]:
           - Success: Returns new position dictionary (containing stock quantity and cash balance)
           - Failure: Returns {"error": error message, ...} dictionary
-        
+
     Raises:
         ValueError: Raised when SIGNATURE environment variable is not set
-        
+
     Example:
         >>> result = sell("AAPL", 10)
         >>> print(result)  # {"AAPL": 90, "MSFT": 5, "CASH": 15000.0, ...}
     """
     # Step 1: Get environment variables and basic information
-    # Get signature (model name) from environment variable, used to determine data storage path
-    signature = get_config_value("SIGNATURE")
+    # Get signature (model name) from parameter or fallback to config/env
     if signature is None:
-        raise ValueError("SIGNATURE environment variable is not set")
-    
-    # Get current trading date from environment variable
-    today_date = get_config_value("TODAY_DATE")
+        signature = get_config_value("SIGNATURE")
+    if signature is None:
+        raise ValueError("SIGNATURE not provided and environment variable is not set")
+
+    # Get current trading date from parameter or fallback to config/env
+    if today_date is None:
+        today_date = get_config_value("TODAY_DATE")
     
     # Step 2: Get current latest position and operation ID
     # get_latest_position returns two values: position dictionary and current maximum operation ID

api/database.py

@@ -438,12 +438,19 @@ def _create_indexes(cursor: sqlite3.Cursor) -> None:
     """)
 
     # Positions table - add index for simulation_run_id and session_id
-    cursor.execute("""
-        CREATE INDEX IF NOT EXISTS idx_positions_run_id ON positions(simulation_run_id)
-    """)
-    cursor.execute("""
-        CREATE INDEX IF NOT EXISTS idx_positions_session_id ON positions(session_id)
-    """)
+    # Check if columns exist before creating indexes
+    cursor.execute("PRAGMA table_info(positions)")
+    position_columns = [row[1] for row in cursor.fetchall()]
+
+    if 'simulation_run_id' in position_columns:
+        cursor.execute("""
+            CREATE INDEX IF NOT EXISTS idx_positions_run_id ON positions(simulation_run_id)
+        """)
+
+    if 'session_id' in position_columns:
+        cursor.execute("""
+            CREATE INDEX IF NOT EXISTS idx_positions_session_id ON positions(session_id)
+        """)
 
 
 def drop_all_tables(db_path: str = "data/jobs.db") -> None:

api/model_day_executor.py

@@ -126,7 +126,7 @@ class ModelDayExecutor:
             os.environ["RUNTIME_ENV_PATH"] = self.runtime_config_path
 
             # Initialize agent
-            agent = self._initialize_agent()
+            agent = await self._initialize_agent()
 
             # Run trading session
             logger.info(f"Running trading session for {self.model_sig} on {self.date}")
@@ -209,7 +209,7 @@ class ModelDayExecutor:
         """Execute model-day simulation (sync entry point)."""
         return self.execute_sync()
 
-    def _initialize_agent(self):
+    async def _initialize_agent(self):
         """
         Initialize trading agent with config.
 
@@ -259,6 +259,9 @@ class ModelDayExecutor:
         # - Database initialization is handled by JobManager
         # - File-based position tracking is only for standalone/CLI mode
 
+        # Initialize MCP client and AI model
+        await agent.initialize()
+
         return agent
 
     def _create_trading_session(self, cursor) -> int:

docker-compose.yml

@@ -7,7 +7,6 @@ services:
     container_name: ai-trader-server
     volumes:
       - ${VOLUME_PATH:-.}/data:/app/data
-      - ${VOLUME_PATH:-.}/logs:/app/logs
       # User configs mounted to /app/user-configs (default config baked into image)
       - ${VOLUME_PATH:-.}/configs:/app/user-configs
     environment:

docs/DOCKER.md

@@ -112,10 +112,9 @@ docker-compose up
 
 ### Volume Mounts
 
-Docker Compose mounts three volumes for persistent data. By default, these are stored in the project directory:
+Docker Compose mounts two volumes for persistent data. By default, these are stored in the project directory:
 
 - `./data:/app/data` - Price data and trading records
-- `./logs:/app/logs` - MCP service logs
 - `./configs:/app/configs` - Configuration files (allows editing configs without rebuilding)
 
 ### Custom Volume Location
@@ -132,7 +131,6 @@ VOLUME_PATH=./volumes
 
 This will store data in:
 - `/home/user/trading-data/data/`
-- `/home/user/trading-data/logs/`
 - `/home/user/trading-data/configs/`
 
 **Note:** The directory structure is automatically created. You'll need to copy your existing configs:
@@ -148,7 +146,7 @@ To reset all trading data:
 
 ```bash
 docker-compose down
-rm -rf ${VOLUME_PATH:-.}/data/agent_data/* ${VOLUME_PATH:-.}/logs/*
+rm -rf ${VOLUME_PATH:-.}/data/agent_data/*
 docker-compose up
 ```
 
@@ -175,8 +173,7 @@ docker pull ghcr.io/xe138/ai-trader-server:latest
 ```bash
 docker run --env-file .env \
   -v $(pwd)/data:/app/data \
-  -v $(pwd)/logs:/app/logs \
-  -p 8000-8003:8000-8003 \
+  -p 8080:8080 \
   ghcr.io/xe138/ai-trader-server:latest
 ```
 
@@ -192,9 +189,9 @@ docker pull ghcr.io/xe138/ai-trader-server:v1.0.0
 **Symptom:** Container exits immediately or errors about ports
 
 **Solutions:**
-- Check ports 8000-8003 not already in use: `lsof -i :8000-8003`
 - View container logs: `docker-compose logs`
-- Check MCP service logs: `cat logs/math.log`
+- Check if API port 8080 is already in use: `lsof -i :8080`
+- Verify MCP services started by checking Docker logs for service startup messages
 
 ### Missing API Keys
 
@@ -216,12 +213,12 @@ docker pull ghcr.io/xe138/ai-trader-server:v1.0.0
 
 ### Permission Issues
 
-**Symptom:** Cannot write to data or logs directories
+**Symptom:** Cannot write to data directory
 
 **Solutions:**
-- Ensure directories writable: `chmod -R 755 data logs`
+- Ensure data directory is writable: `chmod -R 755 data`
 - Check volume mount permissions
-- May need to create directories first: `mkdir -p data logs`
+- May need to create directory first: `mkdir -p data`
 
 ### Container Keeps Restarting
 
@@ -256,13 +253,12 @@ docker buildx build --platform linux/amd64,linux/arm64 -t ai-trader-server .
 docker stats ai-trader-server
 ```
 
-### Access MCP Services Directly
+### Access API Directly
 
-Services exposed on host:
-- Math: http://localhost:8000
-- Search: http://localhost:8001
-- Trade: http://localhost:8002
-- Price: http://localhost:8003
+API server exposed on host:
+- REST API: http://localhost:8080
+
+MCP services run internally and are not exposed to the host.
 
 ## Development Workflow