additional mcp-adapter without RAG logic

backend/agent/coding_agent.py

@@ -383,7 +383,7 @@ class CodingAgent:
         self.api_key = os.getenv("API_KEY")
         self.model   = os.getenv("MODEL")
 
-    async def _call_api(self, messages: list, relevant_tools: list = None) -> str:
+    async def _call_api(self, messages: list) -> str:
         """Make a raw API call and return the response content string."""
         
         headers = {"Content-Type": "application/json"}
@@ -393,7 +393,6 @@ class CodingAgent:
         payload = {
             "model": self.model,
             "messages": messages,
-            "tools": relevant_tools,
             "temperature": 0.2,
             "max_tokens": 4096,
             "stream": False,
@@ -447,10 +446,25 @@ class CodingAgent:
         current_context = self.messages[-1]["content"] if self.messages else ""
         self.iteration += 1
         self.messages = trim_messages(self.messages)
-        relevant_tools = await get_tools_for_prompt(current_context)
+
+        tool_prompt = await get_tools_for_prompt(current_context)
+        
+        enhanced_messages = self.messages.copy()
+        
+        enhanced_messages.append({
+            "role": "system",
+            "content": f"""
+        Available tools for this step:
+        
+        {tool_prompt}
+        
+        You MUST choose one of these tools.
+        """
+        })
+        
 
         try:
-            raw = await self._call_api(self.messages, relevant_tools)
+            raw = await self._call_api(enhanced_messages)
             raw = _strip_code_fences(raw)
             action = json.loads(raw)
         except json.JSONDecodeError:

backend/agent/mcp_server_adapter.py

@@ -1,49 +1,47 @@
 import asyncio
 import json
-# import os
-import numpy as np
 from typing import List, Dict, Any
 from pathlib import Path
 
-from sentence_transformers import SentenceTransformer # embedder
 from mcp import ClientSession, StdioServerParameters
 from mcp.client.stdio import stdio_client
 
-class MCPToolRAGAdapter:
+class MCPToolAdapter:
     def __init__(self, config_path: str = "mcp_server_config.json"):
         self.config_path = config_path
-        self.tools = []
-        self.toolnames = []
-        self.embedder = SentenceTransformer('all-MiniLM-L6-v2') # for embedding tool descriptions
-        self.sessions = {}
-        self.exit_stack = {}
-        self.tool_registry = {}
-        self.tool_embeddings = None
+        self.sessions: Dict[str, ClientSession] = {}
+        self.exit_stack: Dict[str, Any] = {}
+        self.tool_registry: List[Dict[str, Any]] = []
 
     def _load_config(self) -> Dict[str, Any]:
-        config_path = Path(__file__).parent / self.config_path
-        if not config_path.exists():
+        """Lädt die Server-Konfiguration aus der JSON-Datei."""
+        path = Path(__file__).parent / self.config_path
+        if not path.exists():
+            print(f"Config file not found: {path}")
             return {}
         
         try:
-            with open(self.config_path, 'r') as f:
+            with open(path, 'r') as f:
                 return json.load(f)
         except json.JSONDecodeError as e:
             print(f"Error decoding JSON config: {e}")
             return {}
 
     async def initialize_all_sessions(self):
-        """Initialize all MCP sessions defined in the config file and index their tools."""
+        """Initialisiert alle konfigurierten MCP-Sessions und registriert die Tools."""
         config = self._load_config()
+        
         for server_name, params in config.items():
-            print(f"initializing session for {server_name} with params: {params}")
+            print(f"Initializing session for {server_name}...")
+            
             server_params = StdioServerParameters(
-                commanf=params["command"],
+                command=params["command"],
                 args=params.get("args", []),
-                # env=params.get("env", {}),
+                env=params.get("env", None),
             )
             
-            # Verbindung aufbauen (Kontext-Manager manuell handhaben für Langzeit-Sessions)
+            try:
+                # Verbindung aufbauen
                 transport_gen = stdio_client(server_params)
                 read, write = await transport_gen.__aenter__()
                 session = ClientSession(read, write)
@@ -51,64 +49,57 @@ class MCPToolRAGAdapter:
                 await session.initialize()
 
                 self.sessions[server_name] = session
-            self.exit_stack[server_name] = (transport_gen, session)    # Zum späteren sauberen Schließen speichern
-            print(f"Session for {server_name} initialized successfully.")
+                # Speichern für den Shutdown
+                self.exit_stack[server_name] = (transport_gen, session)
 
-            # call tools and index thme
+                # Tools abrufen und registrieren
                 result = await session.list_tools()
-            tools = result.get("tools", [])
+                # result ist oft ein Objekt, wir greifen auf das .tools Attribut zu
+                tools = getattr(result, 'tools', [])
 
                 for tool in tools:
+                    # 'tool' ist hier meist ein Tool-Objekt vom MCP SDK
                     self.tool_registry.append({
                         "server": server_name,
-                    "tool_name": tool["name"],
-                    "definition": tool,
-                    "search_text": f"{tool['name']}: {tool.get('description', '')}",
+                        "name": tool.name,
+                        "definition": tool
                     })
-                self.tool_names.append(tool["name"])
                 
-        # embeddings for all tools in this session
-        if self.tool_registry:
-            texts = [t["search_text"] for t in self.tool_registry]
-            self.tool_embeddings = self.embedder.encode(texts)
-            print(f"Indexing completed. {len(texts)} tools ready.")
+                print(f"Session for {server_name} ready. {len(tools)} tools found.")
 
-    def get_relevant_tools(self, query: str, top_k: int = 5) -> List[Dict[str, Any]]:
-        """Given a user query, return the most relevant tools based on semantic similarity."""
-        if not self.tool_embeddings or not self.tool_registry:
-            print("No tools indexed yet.")
-            return []
+            except Exception as e:
+                print(f"Failed to initialize {server_name}: {e}")
 
-        query_embedding = self.embedder.encode([query])
-        similarities = np.dot(self.tool_embeddings, query_embedding.T).flatten()
-        top_indices = np.argsort(similarities)[-top_k:][::-1]
+    def get_all_tools(self) -> List[Dict[str, Any]]:
+        """Gibt alle gesammelten Tools zurück."""
+        return self.tool_registry
 
-        relevant_tools = [self.tool_registry[i] for i in top_indices]
+    async def call_tool(self, tool_name: str, arguments: Dict[str, Any]):
+        """Findet den richtigen Server für ein Tool und führt es aus."""
+        # Suche in der Registry nach dem passenden Server
+        tool_entry = next((t for t in self.tool_registry if t["name"] == tool_name), None)
         
-        return relevant_tools
+        if not tool_entry:
+            return f"Error: Tool '{tool_name}' not found in registry."
 
-    async def call_tool(self, tool_name: str, arguments: Dict):
-        """ Finds the right server for the tool and calls it with the provided arguments. """
-        for item in self.tool_registry:
-            if item["definition"].name == tool_name:
-                server_name = item["server"]
+        server_name = tool_entry["server"]
         session = self.sessions.get(server_name)
+
         if session:
             try:
                 result = await session.call_tool(tool_name, arguments)
                 return result
             except Exception as e:
-                        print(f"Error calling tool {tool_name} on server {server_name}: {e}")
-                        return f"Error calling tool: {e}"
+                return f"Error calling tool '{tool_name}' on server '{server_name}': {str(e)}"
         
-        return f"Tool '{tool_name}' not found in registry."
+        return f"Error: Session for server '{server_name}' not active."
 
     async def shutdown_all_sessions(self):
-        """Gracefully shutdown all MCP sessions."""
+        """Schließt alle offenen Verbindungen sauber."""
         for server_name, (transport_gen, session) in self.exit_stack.items():
             try:
                 await session.__aexit__(None, None, None)
                 await transport_gen.__aexit__(None, None, None)
-                print(f"Session for {server_name} shut down successfully.")
+                print(f"Session for {server_name} shut down.")
             except Exception as e:
-                print(f"Error shutting down session for {server_name}: {e}")
+                print(f"Error during shutdown of {server_name}: {e}")

backend/agent/mcp_server_adapter_RAG.py

@@ -0,0 +1,114 @@
+import  asyncio
+import json
+# import os
+import numpy as np
+from typing import List, Dict, Any
+from pathlib import Path
+
+from sentence_transformers import SentenceTransformer # embedder
+from mcp import ClientSession, StdioServerParameters
+from mcp.client.stdio import stdio_client
+
+class MCPToolRAGAdapter:
+    def __init__ (self, config_path: str = "mcp_server_config.json"):
+        self.config_path = config_path
+        self.tools = []
+        self.toolnames = []
+        self.embedder = SentenceTransformer('all-MiniLM-L6-v2') # for embedding tool descriptions
+        self.sessions = {}
+        self.exit_stack = {}
+        self.tool_registry = {}
+        self.tool_embeddings = None
+    
+    def _load_config(self) -> Dict[str, Any]:
+        config_path = Path(__file__).parent / self.config_path
+        if not config_path.exists():
+            return {}
+        
+        try:
+            with open(self.config_path, 'r') as f:
+             return json.load(f)
+        except json.JSONDecodeError as e:
+            print(f"Error decoding JSON config: {e}")
+            return {}
+    
+    async def initialize_all_sessions(self):
+        """Initialize all MCP sessions defined in the config file and index their tools."""
+        config = self._load_config()
+        for server_name, params in config.items():
+            print(f"initializing session for {server_name} with params: {params}")
+            server_params = StdioServerParameters(
+                commanf=params["command"],
+                args=params.get("args", []),
+                # env=params.get("env", {}),
+            )
+            
+            # Verbindung aufbauen (Kontext-Manager manuell handhaben für Langzeit-Sessions)
+            transport_gen = stdio_client(server_params)
+            read, write = await transport_gen.__aenter__()
+            session = ClientSession(read, write)
+            await session.__aenter__()
+            await session.initialize()
+
+            self.sessions[server_name] = session
+            self.exit_stack[server_name] = (transport_gen, session)    # Zum späteren sauberen Schließen speichern
+            print(f"Session for {server_name} initialized successfully.")
+
+            # call tools and index thme
+            result = await session.list_tools()
+            tools = result.get("tools", [])
+
+            for tool in tools:
+                self.tool_registry.append({
+                    "server": server_name,
+                    "tool_name": tool["name"],
+                    "definition": tool,
+                    "search_text": f"{tool['name']}: {tool.get('description', '')}",
+                })
+                self.tool_names.append(tool["name"])
+            
+        # embeddings for all tools in this session
+        if self.tool_registry:
+            texts = [t["search_text"] for t in self.tool_registry]
+            self.tool_embeddings = self.embedder.encode(texts)
+            print(f"Indexing completed. {len(texts)} tools ready.")
+
+    def get_relevant_tools(self, query: str, top_k: int = 5) -> List[Dict[str, Any]]:
+        """Given a user query, return the most relevant tools based on semantic similarity."""
+        if not self.tool_embeddings or not self.tool_registry:
+            print("No tools indexed yet.")
+            return []
+        
+        query_embedding = self.embedder.encode([query])
+        similarities = np.dot(self.tool_embeddings, query_embedding.T).flatten()
+        top_indices = np.argsort(similarities)[-top_k:][::-1]
+
+        relevant_tools = [self.tool_registry[i] for i in top_indices]
+
+        return relevant_tools
+    
+    async def call_tool(self, tool_name: str, arguments: Dict):
+        """ Finds the right server for the tool and calls it with the provided arguments. """
+        for item in self.tool_registry:
+            if item["definition"].name == tool_name:
+                server_name = item["server"]
+                session = self.sessions.get(server_name)
+                if session:
+                    try:
+                        result = await session.call_tool(tool_name, arguments)
+                        return result
+                    except Exception as e:
+                        print(f"Error calling tool {tool_name} on server {server_name}: {e}")
+                        return f"Error calling tool: {e}"
+        
+        return f"Tool '{tool_name}' not found in registry."
+    
+    async def shutdown_all_sessions(self):
+        """Gracefully shutdown all MCP sessions."""
+        for server_name, (transport_gen, session) in self.exit_stack.items():
+            try:
+                await session.__aexit__(None, None, None)
+                await transport_gen.__aexit__(None, None, None)
+                print(f"Session for {server_name} shut down successfully.")
+            except Exception as e:
+                print(f"Error shutting down session for {server_name}: {e}")