Refactor and enhance MCP client and server functionality

- Removed prueba_cliente_mcp.py as it was no longer needed.
- Updated prueba_loop_agente.py to integrate MCPServerRunner for managing server instances.
- Modified prueba_mcp.py to implement a new structure for starting and stopping MCP servers.
- Enhanced AgenteAI class to support multiple MCP blocks execution.
- Improved MCPClient with timeout handling for tool calls.
- Added new sandbox files for children's stories.
- Created a simple ERP system with a main entry point.
- Added unit tests for the ERP system.
- Implemented MCPServerRunner to manage server processes.
- Developed server_files.py to handle file operations securely within a sandbox environment.
- Introduced ElementoWeb and Navegador classes for web scraping functionalities.
- Enhanced Scrapper and Tab classes for better interaction with web pages.

prueba_loop_agente.py

@@ -14,6 +14,7 @@ from src.Llms.MCPs.McpClient_Registry import ClientRegistry  # o ajusta según t
 from src.Credenciales.ollama_credencial import OllamaCredencial
 from src.ConexionApis.Ollama_cliente import OllamaCliente
 from src.Llms.Modelos.Ollama_model import ModeloOllama
+from src.Llms.MCPs.McpServer import MCPServerRunner
 
 import asyncio
 
@@ -22,32 +23,60 @@ async def main():
 
     # # Usar Credencial openai
 
-    # conexion_admin = PostgresConexion(db_credencial)
-    # repo = OpenAICredencialRepo(conexion_admin)
-    # credencial_openai = repo.get_by_id("OPAK20250513-61b29978b7604031014")
-    # if credencial_openai is None:
-    #     raise ValueError("No se encontró la credencial OpenAI con el ID proporcionado.")
-    # cliente = OpenAICliente(credencial_openai)
+    conexion_admin = PostgresConexion(db_credencial)
+    repo = OpenAICredencialRepo(conexion_admin)
+    credencial_openai = repo.get_by_id("OPAK20250513-61b29978b7604031014")
+    if credencial_openai is None:
+        raise ValueError("No se encontró la credencial OpenAI con el ID proporcionado.")
+    cliente = OpenAICliente(credencial_openai)
+
+
+    # # Llamamos a los servidores para iniciarlos
+
+    # venv_python = r"E:\Fitz_Studio\.venv\Scripts\python.exe"
+
+    # # runner_math = MCPServerRunner(
+    # #     r"E:\Fitz_Studio\src\Llms\MCPs\McpServers\server_math.py",
+    # #     python_path=venv_python
+    # # )
+    # # runner_tools = MCPServerRunner(
+    # #     r"E:\Fitz_Studio\src\Llms\MCPs\McpServers\server_utils.py",
+    # #     python_path=venv_python
+    # # )
+    # runner_files = MCPServerRunner(
+    #     r"E:\Fitz_Studio\src\Llms\MCPs\McpServers\server_files.py",
+    #     python_path=venv_python
+    # )
+
+
+    # # await runner_math.start()
+    # # await runner_tools.start()
+    # await runner_files.start()
+
+    # # Esperamos un poco para asegurarnos de que los servidores estén listos
+    # await asyncio.sleep(2) 
+
+
 
 
     # Usar Credencial ollama
-    credencial_ollama = OllamaCredencial(titulo="Ollama")
+    # credencial_ollama = OllamaCredencial(titulo="Ollama")
 
-    cliente = OllamaCliente(credencial_ollama)
+    # cliente = OllamaCliente(credencial_ollama)
 
-    modelo = ModeloOllama(
-        cliente=cliente,
-        model="llama3.1:8b")
+    # modelo = ModeloOllama(
+    #     cliente=cliente,
+    #     model="llama3.1:8b")
     
 
 
     # # crea el modelo (openai)
 
-    # modelo = ModeloOpenAI(
-    #     cliente=cliente,
-    #     model="gpt-4o",
-    #     temperature=1
-    # )
+    modelo = ModeloOpenAI(
+        cliente=cliente,
+        model="gpt-4o",
+        temperature=1
+    )
 
     # Le otorga memoria 
 
@@ -60,24 +89,30 @@ async def main():
 
     # Cargamos las herramientas
 
-    herramientas = MCPClient.from_http(
-        name="tools",
-        url="http://127.0.0.1:4300/tools/"
+    # herramientas = MCPClient.from_http(
+    #     name="tools",
+    #     url="http://127.0.0.1:4300/tools/"
+    # )
+
+    # math = MCPClient.from_http(
+    #     name="math",
+    #     url="http://127.0.0.1:4200/math/"
+    # )
+
+    archivos = MCPClient.from_http(
+        name="files",
+        url="http://127.0.0.1:4201/fs"
     )
 
-    math = MCPClient.from_http(
-        name="math",
-        url="http://127.0.0.1:4200/math/"
-    )
 
     # Las añadimos al registro de herramientas
 
     registry = ClientRegistry()
 
 
-    registry.add("tools", herramientas)
-    registry.add("math", math)
-
+    # registry.add("tools", herramientas)
+    # registry.add("math", math)
+    registry.add("files", archivos)
 
 
     # --- INICIALIZACIÓN DEL AGENTE ---
@@ -98,7 +133,7 @@ async def main():
         ],
 
         max_iterations=0,
-        # memoria=memoria,
+        memoria=memoria,
         
         mcp=registry  # ← ✅ Integración del cliente MCP
     )
@@ -133,6 +168,3 @@ async def main():
 if __name__ == "__main__":
     asyncio.run(main())
 
-
-
-