Restructured Folder

agentic-workflows/misc/combined.proto

+syntax = "proto3";
+
+package combined;
+
+// Shared empty message
+message Empty {}
+
+// Shared enum AgentType
+enum AgentType {
+  UNKNOWN = 0;
+  WEBSCRAPER = 1;
+  PLACES = 2;
+  WEATHER = 3;
+  NEWS = 4;
+  WIKI = 5;
+  URBAN_PLANNING = 6;
+  OTHER = 7;
+}
+
+// Shared messages
+message FunctionSchemasResponse {
+  AgentType agent_type = 1;
+  repeated string function_schemas = 2;
+}
+
+message ToolRequest {
+  AgentType agent_type = 1;
+  string tool_name = 2;
+  string arguments_json = 3;
+}
+
+message ToolInvocationResult {
+  AgentType agent_type = 1;
+  repeated string results = 2;
+}
+
+// Unique message from llm.proto
+message UserMessage {
+  string message = 1;
+}
+
+// Services
+service ToolService {
+  rpc SendFunctionSchemas (Empty) returns (stream FunctionSchemasResponse);
+  rpc InvokeTool (stream ToolRequest) returns (stream ToolInvocationResult);
+}
+
+service LLM {
+  rpc GetUserQuery (stream UserMessage) returns (Empty);
+  rpc GetFuncSchemas (stream FunctionSchemasResponse) returns (stream ToolRequest);
+  rpc RecvCallTool (stream ToolInvocationResult) returns (stream ToolInvocationResult);
+}

agentic-workflows/misc/combined_pb2.py

+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# NO CHECKED-IN PROTOBUF GENCODE
+# source: combined.proto
+# Protobuf Python Version: 5.29.0
+"""Generated protocol buffer code."""
+from google.protobuf import descriptor as _descriptor
+from google.protobuf import descriptor_pool as _descriptor_pool
+from google.protobuf import runtime_version as _runtime_version
+from google.protobuf import symbol_database as _symbol_database
+from google.protobuf.internal import builder as _builder
+_runtime_version.ValidateProtobufRuntimeVersion(
+    _runtime_version.Domain.PUBLIC,
+    5,
+    29,
+    0,
+    '',
+    'combined.proto'
+)
+# @@protoc_insertion_point(imports)
+
+_sym_db = _symbol_database.Default()
+
+
+
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\x0e\x63ombined.proto\x12\x08\x63ombined\"\x07\n\x05\x45mpty\"\\\n\x17\x46unctionSchemasResponse\x12\'\n\nagent_type\x18\x01 \x01(\x0e\x32\x13.combined.AgentType\x12\x18\n\x10\x66unction_schemas\x18\x02 \x03(\t\"a\n\x0bToolRequest\x12\'\n\nagent_type\x18\x01 \x01(\x0e\x32\x13.combined.AgentType\x12\x11\n\ttool_name\x18\x02 \x01(\t\x12\x16\n\x0e\x61rguments_json\x18\x03 \x01(\t\"P\n\x14ToolInvocationResult\x12\'\n\nagent_type\x18\x01 \x01(\x0e\x32\x13.combined.AgentType\x12\x0f\n\x07results\x18\x02 \x03(\t\"\x1e\n\x0bUserMessage\x12\x0f\n\x07message\x18\x01 \x01(\t*t\n\tAgentType\x12\x0b\n\x07UNKNOWN\x10\x00\x12\x0e\n\nWEBSCRAPER\x10\x01\x12\n\n\x06PLACES\x10\x02\x12\x0b\n\x07WEATHER\x10\x03\x12\x08\n\x04NEWS\x10\x04\x12\x08\n\x04WIKI\x10\x05\x12\x12\n\x0eURBAN_PLANNING\x10\x06\x12\t\n\x05OTHER\x10\x07\x32\xa3\x01\n\x0bToolService\x12K\n\x13SendFunctionSchemas\x12\x0f.combined.Empty\x1a!.combined.FunctionSchemasResponse0\x01\x12G\n\nInvokeTool\x12\x15.combined.ToolRequest\x1a\x1e.combined.ToolInvocationResult(\x01\x30\x01\x32\xe3\x01\n\x03LLM\x12\x38\n\x0cGetUserQuery\x12\x15.combined.UserMessage\x1a\x0f.combined.Empty(\x01\x12N\n\x0eGetFuncSchemas\x12!.combined.FunctionSchemasResponse\x1a\x15.combined.ToolRequest(\x01\x30\x01\x12R\n\x0cRecvCallTool\x12\x1e.combined.ToolInvocationResult\x1a\x1e.combined.ToolInvocationResult(\x01\x30\x01\x62\x06proto3')
+
+_globals = globals()
+_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
+_builder.BuildTopDescriptorsAndMessages(DESCRIPTOR, 'combined_pb2', _globals)
+if not _descriptor._USE_C_DESCRIPTORS:
+  DESCRIPTOR._loaded_options = None
+  _globals['_AGENTTYPE']._serialized_start=344
+  _globals['_AGENTTYPE']._serialized_end=460
+  _globals['_EMPTY']._serialized_start=28
+  _globals['_EMPTY']._serialized_end=35
+  _globals['_FUNCTIONSCHEMASRESPONSE']._serialized_start=37
+  _globals['_FUNCTIONSCHEMASRESPONSE']._serialized_end=129
+  _globals['_TOOLREQUEST']._serialized_start=131
+  _globals['_TOOLREQUEST']._serialized_end=228
+  _globals['_TOOLINVOCATIONRESULT']._serialized_start=230
+  _globals['_TOOLINVOCATIONRESULT']._serialized_end=310
+  _globals['_USERMESSAGE']._serialized_start=312
+  _globals['_USERMESSAGE']._serialized_end=342
+  _globals['_TOOLSERVICE']._serialized_start=463
+  _globals['_TOOLSERVICE']._serialized_end=626
+  _globals['_LLM']._serialized_start=629
+  _globals['_LLM']._serialized_end=856
+# @@protoc_insertion_point(module_scope)

agentic-workflows/misc/combined_pb2_grpc.py

+# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
+"""Client and server classes corresponding to protobuf-defined services."""
+import grpc
+import warnings
+
+import combined_pb2 as combined__pb2
+
+GRPC_GENERATED_VERSION = '1.71.0'
+GRPC_VERSION = grpc.__version__
+_version_not_supported = False
+
+try:
+    from grpc._utilities import first_version_is_lower
+    _version_not_supported = first_version_is_lower(GRPC_VERSION, GRPC_GENERATED_VERSION)
+except ImportError:
+    _version_not_supported = True
+
+if _version_not_supported:
+    raise RuntimeError(
+        f'The grpc package installed is at version {GRPC_VERSION},'
+        + f' but the generated code in combined_pb2_grpc.py depends on'
+        + f' grpcio>={GRPC_GENERATED_VERSION}.'
+        + f' Please upgrade your grpc module to grpcio>={GRPC_GENERATED_VERSION}'
+        + f' or downgrade your generated code using grpcio-tools<={GRPC_VERSION}.'
+    )
+
+
+class ToolServiceStub(object):
+    """Services
+    """
+
+    def __init__(self, channel):
+        """Constructor.
+
+        Args:
+            channel: A grpc.Channel.
+        """
+        self.SendFunctionSchemas = channel.unary_stream(
+                '/combined.ToolService/SendFunctionSchemas',
+                request_serializer=combined__pb2.Empty.SerializeToString,
+                response_deserializer=combined__pb2.FunctionSchemasResponse.FromString,
+                _registered_method=True)
+        self.InvokeTool = channel.stream_stream(
+                '/combined.ToolService/InvokeTool',
+                request_serializer=combined__pb2.ToolRequest.SerializeToString,
+                response_deserializer=combined__pb2.ToolInvocationResult.FromString,
+                _registered_method=True)
+
+
+class ToolServiceServicer(object):
+    """Services
+    """
+
+    def SendFunctionSchemas(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def InvokeTool(self, request_iterator, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+
+def add_ToolServiceServicer_to_server(servicer, server):
+    rpc_method_handlers = {
+            'SendFunctionSchemas': grpc.unary_stream_rpc_method_handler(
+                    servicer.SendFunctionSchemas,
+                    request_deserializer=combined__pb2.Empty.FromString,
+                    response_serializer=combined__pb2.FunctionSchemasResponse.SerializeToString,
+            ),
+            'InvokeTool': grpc.stream_stream_rpc_method_handler(
+                    servicer.InvokeTool,
+                    request_deserializer=combined__pb2.ToolRequest.FromString,
+                    response_serializer=combined__pb2.ToolInvocationResult.SerializeToString,
+            ),
+    }
+    generic_handler = grpc.method_handlers_generic_handler(
+            'combined.ToolService', rpc_method_handlers)
+    server.add_generic_rpc_handlers((generic_handler,))
+    server.add_registered_method_handlers('combined.ToolService', rpc_method_handlers)
+
+
+ # This class is part of an EXPERIMENTAL API.
+class ToolService(object):
+    """Services
+    """
+
+    @staticmethod
+    def SendFunctionSchemas(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_stream(
+            request,
+            target,
+            '/combined.ToolService/SendFunctionSchemas',
+            combined__pb2.Empty.SerializeToString,
+            combined__pb2.FunctionSchemasResponse.FromString,
+            options,
+            channel_credentials,
+            insecure,
+            call_credentials,
+            compression,
+            wait_for_ready,
+            timeout,
+            metadata,
+            _registered_method=True)
+
+    @staticmethod
+    def InvokeTool(request_iterator,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.stream_stream(
+            request_iterator,
+            target,
+            '/combined.ToolService/InvokeTool',
+            combined__pb2.ToolRequest.SerializeToString,
+            combined__pb2.ToolInvocationResult.FromString,
+            options,
+            channel_credentials,
+            insecure,
+            call_credentials,
+            compression,
+            wait_for_ready,
+            timeout,
+            metadata,
+            _registered_method=True)
+
+
+class LLMStub(object):
+    """Missing associated documentation comment in .proto file."""
+
+    def __init__(self, channel):
+        """Constructor.
+
+        Args:
+            channel: A grpc.Channel.
+        """
+        self.GetUserQuery = channel.stream_unary(
+                '/combined.LLM/GetUserQuery',
+                request_serializer=combined__pb2.UserMessage.SerializeToString,
+                response_deserializer=combined__pb2.Empty.FromString,
+                _registered_method=True)
+        self.GetFuncSchemas = channel.stream_stream(
+                '/combined.LLM/GetFuncSchemas',
+                request_serializer=combined__pb2.FunctionSchemasResponse.SerializeToString,
+                response_deserializer=combined__pb2.ToolRequest.FromString,
+                _registered_method=True)
+        self.RecvCallTool = channel.stream_stream(
+                '/combined.LLM/RecvCallTool',
+                request_serializer=combined__pb2.ToolInvocationResult.SerializeToString,
+                response_deserializer=combined__pb2.ToolInvocationResult.FromString,
+                _registered_method=True)
+
+
+class LLMServicer(object):
+    """Missing associated documentation comment in .proto file."""
+
+    def GetUserQuery(self, request_iterator, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def GetFuncSchemas(self, request_iterator, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def RecvCallTool(self, request_iterator, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+
+def add_LLMServicer_to_server(servicer, server):
+    rpc_method_handlers = {
+            'GetUserQuery': grpc.stream_unary_rpc_method_handler(
+                    servicer.GetUserQuery,
+                    request_deserializer=combined__pb2.UserMessage.FromString,
+                    response_serializer=combined__pb2.Empty.SerializeToString,
+            ),
+            'GetFuncSchemas': grpc.stream_stream_rpc_method_handler(
+                    servicer.GetFuncSchemas,
+                    request_deserializer=combined__pb2.FunctionSchemasResponse.FromString,
+                    response_serializer=combined__pb2.ToolRequest.SerializeToString,
+            ),
+            'RecvCallTool': grpc.stream_stream_rpc_method_handler(
+                    servicer.RecvCallTool,
+                    request_deserializer=combined__pb2.ToolInvocationResult.FromString,
+                    response_serializer=combined__pb2.ToolInvocationResult.SerializeToString,
+            ),
+    }
+    generic_handler = grpc.method_handlers_generic_handler(
+            'combined.LLM', rpc_method_handlers)
+    server.add_generic_rpc_handlers((generic_handler,))
+    server.add_registered_method_handlers('combined.LLM', rpc_method_handlers)
+
+
+ # This class is part of an EXPERIMENTAL API.
+class LLM(object):
+    """Missing associated documentation comment in .proto file."""
+
+    @staticmethod
+    def GetUserQuery(request_iterator,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.stream_unary(
+            request_iterator,
+            target,
+            '/combined.LLM/GetUserQuery',
+            combined__pb2.UserMessage.SerializeToString,
+            combined__pb2.Empty.FromString,
+            options,
+            channel_credentials,
+            insecure,
+            call_credentials,
+            compression,
+            wait_for_ready,
+            timeout,
+            metadata,
+            _registered_method=True)
+
+    @staticmethod
+    def GetFuncSchemas(request_iterator,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.stream_stream(
+            request_iterator,
+            target,
+            '/combined.LLM/GetFuncSchemas',
+            combined__pb2.FunctionSchemasResponse.SerializeToString,
+            combined__pb2.ToolRequest.FromString,
+            options,
+            channel_credentials,
+            insecure,
+            call_credentials,
+            compression,
+            wait_for_ready,
+            timeout,
+            metadata,
+            _registered_method=True)
+
+    @staticmethod
+    def RecvCallTool(request_iterator,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.stream_stream(
+            request_iterator,
+            target,
+            '/combined.LLM/RecvCallTool',
+            combined__pb2.ToolInvocationResult.SerializeToString,
+            combined__pb2.ToolInvocationResult.FromString,
+            options,
+            channel_credentials,
+            insecure,
+            call_credentials,
+            compression,
+            wait_for_ready,
+            timeout,
+            metadata,
+            _registered_method=True)

agentic-workflows/src/MCP-Agents/mcp-web-scraper/mcp_web_scraper.py

 # server.py
 from fastmcp import FastMCP
-
+import random
 import requests
 from bs4 import BeautifulSoup
 import re
@@ -12,23 +12,28 @@ mcp = FastMCP("WebScraper")
 print(f"Starting server {mcp.name}")
 
 
-# Add a web-scraping tool
+USER_AGENTS = [
+    "Mozilla/5.0 (Windows NT 10.0; Win64; x64)...",
+    "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7)...",
+    # add several real user agents here to rotate
+]
+
 @mcp.tool()
 def scrape_and_clean(url: str):
-    """Scrapes and extracts structured content, headings, and text from a webpage."""
-
     try:
         import validators
-
         if not validators.url(url):
             return {"error": "Invalid URL format."}
 
-        headers = {"User-Agent": "Mozilla/5.0 (compatible; WebScraperBot/1.0)"}
-        response = requests.get(url, headers=headers, timeout=10)
+        headers = {
+            "User-Agent": random.choice(USER_AGENTS)
+        }
+        response = requests.get(url, headers=headers, timeout=15)
         response.raise_for_status()
 
         soup = BeautifulSoup(response.content, "html.parser")
 
+        # Remove unwanted tags
         for tag in soup(["script", "style", "noscript", "iframe"]):
             tag.decompose()
 
@@ -54,10 +59,3 @@ def scrape_and_clean(url: str):
 
     except Exception as e:
         return {"error": str(e)}
-
-
-@mcp.prompt()
-def webscraper_prompt(mes_web_scraper: str) -> str:
-    """Create an intelligent webscraper prompt."""
-
-    return f"Extract the main content, headings, and structured data from the following URL or query: '{mes_web_scraper}'."

agentic-workflows/src/MCP-Agents/mcp-web-scraper/requirements.txt

@@ -5,4 +5,5 @@ protobuf
 multithreading
 requests
 fastmcp
-bs4
\ No newline at end of file
+bs4
+validators
\ No newline at end of file

agentic-workflows/src/MCP-Agents/mcp-web-scraper/server.py

@@ -41,7 +41,7 @@ class ToolService(agent_pb2_grpc.ToolServiceServicer):
                 agent_type=agent_pb2.WEBSCRAPER, function_schemas=serialized_schemas
             )
 
-            print("🔄 Sending schema update (heartbeat or change).")
+            #print("Sending schema update (heartbeat or change).")
             yield schema_update
 
     async def InvokeTool(self, request_iterator, context):

agentic-workflows/template/mcp-to-do/build_and_deploy.sh

+#!/bin/bash
+
+# Variables
+IMAGE_NAME="mcp-to-do"
+REGISTRY_URL="cicd.ai4eu-dev.eu:7444"
+REPO_PATH="tutorials/id-aiod-mcp"
+TAG="latest"  
+
+# Step 1: Build the Docker image
+echo "Building Docker image..."
+docker build -t $IMAGE_NAME .
+
+# Step 2: Tag the Docker image
+echo "Tagging Docker image..."
+docker tag $IMAGE_NAME $REGISTRY_URL/$REPO_PATH/$IMAGE_NAME:$TAG
+
+# Step 3: Push the Docker image to the registry
+echo "Pushing Docker image to registry..."
+docker push $REGISTRY_URL/$REPO_PATH/$IMAGE_NAME:$TAG
+
+# Check if the image was pushed successfully
+if [ $? -eq 0 ]; then
+  echo "Docker image successfully pushed to $REGISTRY_URL/$REPO_PATH/$IMAGE_NAME:$TAG"
+else
+  echo "Error: Docker push failed!"
+  exit 1
+fi
\ No newline at end of file

agentic-workflows/template/mcp-to-do/mcp_to_do.py

+from fastmcp import FastMCP
+import random
+from datetime import datetime, timedelta
+
+
+# Initialize MCP server
+mcp = FastMCP("MyToDoList")
+print(f"Starting server {mcp.name}")
+
+task_names = [
+    "Buy groceries", "Read AI research paper", "Write blog post",
+    "Exercise", "Call Mom", "Plan vacation", "Fix bug in code",
+    "Prepare presentation", "Water plants", "Clean the kitchen"
+]
+
+def random_task():
+    name = random.choice(task_names)
+    priority = random.randint(1, 5)  # 1 = highest, 5 = lowest
+    due_date = datetime.now() + timedelta(days=random.randint(0, 10))
+    return {
+        "task": name,
+        "priority": priority,
+        "due": due_date.strftime("%Y-%m-%d")
+    }
+
+@mcp.tool()
+def fetch_my_list():
+    """Return a randomly generated list of tasks."""
+    sample_tasks = [random_task() for _ in range(random.randint(3, 6))]
+    return {"tasks": sample_tasks}

agentic-workflows/template/mcp-to-do/server.py

+import asyncio
+import json
+import grpc
+from fastmcp import Client
+from mcp_to_do import mcp # Change this import accordingly
+
+import agent_pb2
+import agent_pb2_grpc
+
+
+class ToolService(agent_pb2_grpc.ToolServiceServicer):
+    def __init__(self):
+        self.last_sent_function_schemas = None
+
+    async def SendFunctionSchemas(self, request, context):
+        print("Received request for SendFunctionSchemas (streaming).")
+        print(context.peer())
+
+        while True:
+            client = Client(mcp)
+            async with client:
+                available_tools = await client.list_tools()
+
+            serialized_schemas = []
+
+            for tool in available_tools:
+                function_schema_dict = {
+                    "name": tool.name,
+                    "description": tool.description or tool.name,
+                    "parameters": {"type": "object", "properties": {}},
+                    "required": [],
+                }
+
+                if hasattr(tool, "inputSchema") and tool.inputSchema:
+                    if tool.inputSchema.get("type") == "object":
+                        function_schema_dict["parameters"] = tool.inputSchema
+
+                serialized_schemas.append(json.dumps(function_schema_dict))
+
+            schema_update = agent_pb2.FunctionSchemasResponse(
+                agent_type=agent_pb2.OTHER, function_schemas=serialized_schemas  # Add this to the ENUM in the protobuf file
+            )
+
+            # print("Sending schema update (heartbeat or change).")
+            yield schema_update
+
+    async def InvokeTool(self, request_iterator, context):
+        """
+        Processes tool invocation requests from a client stream and returns tool results.
+        """
+        print("📥 Received InvokeTool stream")
+
+        async for tool_request in request_iterator:
+            tool_name = tool_request.tool_name
+            agent_type = tool_request.agent_type  # Enum value, e.g., 1 for WEBSCRAPER
+            arguments = json.loads(tool_request.arguments_json)
+
+            print(f"Invoking tool: {tool_name}")
+            print(f"Arguments as dict: {arguments}")
+            print(f"Agent Type: {agent_type}")
+
+            # Check if the agent type matches YOUR_TOOL_NAME_ENUM
+            if agent_type == agent_pb2.OTHER:
+                try:
+                    client = Client(mcp)
+                    async with client:
+                        tool_result = await client.call_tool(tool_name, arguments)
+
+                    print(f"---**---Tool invocation result: {tool_result}")
+                    yield agent_pb2.ToolInvocationResult(
+                        results=[str(tool_result)], agent_type=agent_type
+                    )
+
+                except Exception as e:
+                    print(f"Failed to invoke tool '{tool_name}': {str(e)}")
+
+            else:
+                print(f"Tool not allowed for agent type {agent_type}, skipping...")
+
+        print("Finished processing all InvokeTool requests.")
+
+
+async def serve():
+    """
+    Starts the gRPC server and listens for incoming requests.
+    """
+    server = grpc.aio.server()
+    agent_pb2_grpc.add_ToolServiceServicer_to_server(ToolService(), server)
+    server.add_insecure_port("[::]:8061")
+    print("--*--gRPC server listening on port 8061...")
+    await server.start()
+    await server.wait_for_termination()
+
+
+if __name__ == "__main__":
+    asyncio.run(serve())

agentic-workflows/template/mcp-tool-name/Dockerfile

+# Use a slim Python base image
+FROM python:3.12-slim
+
+ENV PYTHONUNBUFFERED=1
+
+RUN apt-get update -y && \
+    apt-get install -y --no-install-recommends \
+        build-essential \
+        gcc \
+        libffi-dev \
+        libssl-dev \
+        git \
+        curl \
+        ca-certificates \
+        tzdata \
+        protobuf-compiler && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
+
+# Set timezone
+ARG TIMEZONE=Europe/Berlin
+ENV TZ=$TIMEZONE
+RUN ln -snf /usr/share/zoneinfo/$TIMEZONE /etc/localtime && echo $TIMEZONE > /etc/timezone
+
+# Set working directory
+WORKDIR /weather-agent
+
+# Copy requirements and install
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy project files
+COPY . .
+
+# Compile .proto file
+RUN python3 -m grpc_tools.protoc \
+    -I. \
+    --python_out=. \
+    --grpc_python_out=. \
+    agent.proto
+
+# Run the server
+CMD ["python3", "-u", "server.py"]
+

agentic-workflows/template/mcp-tool-name/agent.proto

+syntax = "proto3";
+
+message Empty {
+  
+}
+
+enum AgentType {
+  UNKNOWN = 0;
+  WEBSCRAPER = 1;
+  PLACES = 2;
+  WEATHER = 3;
+  NEWS = 4;
+  WIKI = 5;
+  URBAN_PLANNING = 6;
+  OTHER = 7;
+  YOUR_TOOL_NAME_ENUM = 8;
+}
+
+
+message FunctionSchemasResponse {
+  AgentType agent_type = 1;
+  repeated string function_schemas = 2;
+}
+
+message ToolRequest {
+  AgentType agent_type = 1;
+  string tool_name = 2;
+  string arguments_json = 3;
+}
+
+message ToolInvocationResult {
+  AgentType agent_type = 1;
+  repeated string results = 2;
+}
+
+service ToolService {
+  rpc SendFunctionSchemas (Empty) returns (stream FunctionSchemasResponse);
+  rpc InvokeTool (stream ToolRequest) returns (stream ToolInvocationResult);
+}

agentic-workflows/template/mcp-tool-name/requirements.txt

+grpcio
+grpcio-tools
+grpc-interceptor
+protobuf
+multithreading
+requests
+fastmcp