diff --git a/Makefile b/Makefile
index d4b393f..cab622a 100644
--- a/Makefile
+++ b/Makefile
@@ -6,4 +6,10 @@ lint:
 	uv run ruff check .
 
 leaderboard:
-	uv run -- streamlit run agents_mcp_usage/multi_mcp/eval_multi_mcp/merbench_ui.py
\ No newline at end of file
+	uv run -- streamlit run agents_mcp_usage/multi_mcp/eval_multi_mcp/merbench_ui.py
+
+adk_basic_ui:
+	uv run adk web agents_mcp_usage/basic_mcp
+
+adk_multi_ui:
+	uv run adk web agents_mcp_usage/multi_mcp
\ No newline at end of file
diff --git a/README.md b/README.md
index f5427e4..8e73b20 100644
--- a/README.md
+++ b/README.md
@@ -38,7 +38,10 @@ Run an Agent framework script e.g.:
 - `uv run agents_mcp_usage/basic_mcp/basic_mcp_use/oai-agent_mcp.py`
   - Requires `OPENAI_API_KEY` by default
 
-Check console or Logfire for output
+- Launch the ADK web UI for visual interaction with the agents:
+  - `make adk_basic_ui`
+  
+Check console, Logfire, or the ADK web UI for output
 
 ## Project Overview
 
@@ -55,7 +58,7 @@ This project aims to teach:
 
 - **[agents_mcp_usage/basic_mcp/](agents_mcp_usage/basic_mcp/)** - Single MCP server integration examples
   - **basic_mcp_use/** - Contains basic examples of single MCP usage:
-    - `adk_mcp.py` - Example of using MCP with Google's Agent Development Kit (ADK)
+    - `adk_mcp.py` - Example of using MCP with Google's Agent Development Kit (ADK 1.3.0)
     - `langgraph_mcp.py` - Example of using MCP with LangGraph
     - `oai-agent_mcp.py` - Example of using MCP with OpenAI Agents
     - `pydantic_mcp.py` - Example of using MCP with Pydantic-AI
@@ -154,6 +157,9 @@ uv run agents_mcp_usage/basic_mcp/basic_mcp_use/oai-agent_mcp.py
 
 # Pydantic-AI example
 uv run agents_mcp_usage/basic_mcp/basic_mcp_use/pydantic_mcp.py
+
+# Launch ADK web UI for visual interaction
+make adk_basic_ui
 ```
 
 More details on basic MCP implementation can be found in the [basic_mcp README](agents_mcp_usage/basic_mcp/README.md).
@@ -218,7 +224,7 @@ uv run agents_mcp_usage/multi_mcp/multi_mcp_use/pydantic_mcp.py
 uv run agents_mcp_usage/multi_mcp/eval_multi_mcp/evals_pydantic_mcp.py
 
 # Run multi-model benchmarking
-uv run agents_mcp_usage/multi_mcp/eval_multi_mcp/run_multi_evals.py --models "gemini-2.5-pro,gemini-2.0-flash" --runs 5 --parallel
+uv run agents_mcp_usage/multi_mcp/eval_multi_mcp/run_multi_evals.py --models "gemini-2.5-pro-preview-06-05,gemini-2.0-flash" --runs 5 --parallel
 
 # Launch the evaluation dashboard
 uv run streamlit run agents_mcp_usage/multi_mcp/eval_multi_mcp/merbench_ui.py
@@ -258,7 +264,7 @@ uv run agents_mcp_usage/multi_mcp/eval_multi_mcp/evals_pydantic_mcp.py
 
 # Multi-model parallel benchmarking
 uv run agents_mcp_usage/multi_mcp/eval_multi_mcp/run_multi_evals.py \
-  --models "gemini-2.5-pro,gemini-2.0-flash,gemini-2.5-flash-preview-04-17" \
+  --models "gemini-2.5-pro-preview-06-05,gemini-2.0-flash,gemini-2.5-flash" \
   --runs 5 \
   --parallel \
   --output-dir ./results
@@ -288,6 +294,11 @@ A key advantage highlighted is flexibility; MCP allows developers to more easily
    ```bash
    make install
    ```
+
+   To use the ADK web UI, run:
+   ```bash
+   make adk_basic_ui
+   ```
 3. Set up your environment variables in a `.env` file:
    ```
    LOGFIRE_TOKEN=your_logfire_token
diff --git a/agents_mcp_usage/basic_mcp/README.md b/agents_mcp_usage/basic_mcp/README.md
index d6aae46..73f1597 100644
--- a/agents_mcp_usage/basic_mcp/README.md
+++ b/agents_mcp_usage/basic_mcp/README.md
@@ -21,6 +21,9 @@ Each script demonstrates how to connect to a single local MCP server and use it
    
    # Run the Google ADK example
    uv run agents_mcp_usage/basic_mcp/basic_mcp_use/adk_mcp.py
+   
+   ## Launch ADK web UI for visual interaction
+   make adk_basic_ui
    ```
 
 4. Check the console output or Logfire for results.
@@ -155,18 +158,25 @@ The sequence diagram illustrates the temporal flow of interactions between the u
 
 **File:** `adk_mcp.py`
 
-This example demonstrates how to use MCP with Google's Agent Development Kit (ADK).
+This example demonstrates how to use MCP with Google's Agent Development Kit (ADK 1.3.0).
 
 ```bash
 uv run agents_mcp_usage/basic_mcp/basic_mcp_use/adk_mcp.py
 ```
 
 Key features:
-- Uses `MCPToolset` for connecting to the MCP server
+- Uses `MCPToolset` with `StdioConnectionParams` for MCP server connection
 - Configures a Gemini model using ADK's `LlmAgent`
 - Sets up session handling and runner for agent execution
+- Implements proper resource management for MCP connections
+- Supports ADK web UI through module exports
 - Includes Logfire instrumentation for tracing
 
+To run with the ADK web UI:
+```bash
+make adk_basic_ui
+```
+
 ### LangGraph
 
 **File:** `langgraph_mcp.py`
diff --git a/agents_mcp_usage/basic_mcp/basic_mcp_use/__init__.py b/agents_mcp_usage/basic_mcp/basic_mcp_use/__init__.py
index 0a49113..86cb9cb 100644
--- a/agents_mcp_usage/basic_mcp/basic_mcp_use/__init__.py
+++ b/agents_mcp_usage/basic_mcp/basic_mcp_use/__init__.py
@@ -1 +1,4 @@
 # Basic MCP usage examples package
+
+# Allow discovery of the ADK agent via the ADK web UI
+from .adk_mcp import root_agent as root_agent
diff --git a/agents_mcp_usage/basic_mcp/basic_mcp_use/adk_mcp.py b/agents_mcp_usage/basic_mcp/basic_mcp_use/adk_mcp.py
index d15ec9d..a3503c6 100644
--- a/agents_mcp_usage/basic_mcp/basic_mcp_use/adk_mcp.py
+++ b/agents_mcp_usage/basic_mcp/basic_mcp_use/adk_mcp.py
@@ -1,14 +1,28 @@
+"""ADK-based agent using MCP protocol for tool access.
+
+This module provides an ADK agent that can be used both in the ADK web UI
+and directly from the command line. The agent uses MCP tools to access
+external functionality.
+"""
+
 import asyncio
 import os
 import logfire
+from typing import List, Tuple, Any
 
 from dotenv import load_dotenv
 from google.adk.agents.llm_agent import LlmAgent
-from google.adk.tools.mcp_tool.mcp_toolset import MCPToolset, StdioServerParameters
+from google.adk.tools.mcp_tool.mcp_toolset import (
+    MCPToolset,
+    StdioServerParameters,
+    StdioConnectionParams,
+)
 from google.adk.runners import Runner
 from google.adk.sessions import InMemorySessionService
 from google.genai import types
 
+from agents_mcp_usage.utils import get_mcp_server_path
+
 load_dotenv()
 
 # Set API key for Google AI API from environment variable
@@ -18,62 +32,149 @@
 logfire.configure(send_to_logfire="if-token-present", service_name="adk-basic-mcp")
 logfire.instrument_mcp()
 
+# Global variable to store toolset instances for cleanup
+_ACTIVE_TOOLSETS = []
 
-async def main(query: str = "Greet Andrew and give him the current time") -> None:
-    """Runs the agent with a given query.
 
-    This function sets up the MCP server, creates an LLM agent, and runs it
-    with a specified query. It also handles the cleanup of the MCP server
-    connection.
+# Initialize the MCP tools and agent for ADK web UI
+async def init_mcp_toolset() -> Tuple[List[Any], List[MCPToolset]]:
+    """Initialize and return the MCP tools and toolsets.
 
-    Args:
-        query: The query to run the agent with.
+    Returns:
+        Tuple[List[Any], List[MCPToolset]]: A tuple of (tools, toolsets)
     """
-    # Set up MCP server connection
+    global _ACTIVE_TOOLSETS
+
+    # Use absolute path to MCP server based on project root
+    mcp_server_path = get_mcp_server_path("example_server.py")
+
     server_params = StdioServerParameters(
         command="uv",
-        args=["run", "mcp_servers/example_server.py", "stdio"],
+        args=["run", str(mcp_server_path), "stdio"],
     )
+    connection_params = StdioConnectionParams(server_params=server_params)
+    toolset = MCPToolset(connection_params=connection_params)
 
-    tools, exit_stack = await MCPToolset.from_server(connection_params=server_params)
-    print(f"Connected to MCP server. Found {len(tools)} tools.")
+    try:
+        tools = await toolset.get_tools()
+        _ACTIVE_TOOLSETS.append(toolset)
+        return tools, [toolset]
+    except Exception as e:
+        # Clean up in case of initialization error
+        try:
+            await toolset.close()
+        except Exception:
+            pass
+        raise e
+
+
+async def cleanup_toolsets():
+    """Clean up any active MCP toolset connections."""
+    global _ACTIVE_TOOLSETS
+
+    for toolset in _ACTIVE_TOOLSETS:
+        try:
+            await toolset.close()
+            print("MCP toolset connection closed.")
+        except asyncio.CancelledError:
+            print("MCP cleanup cancelled - this is normal")
+        except Exception as e:
+            print(f"Warning: Error during toolset cleanup: {e}")
+
+    _ACTIVE_TOOLSETS = []
+
+
+# Define a before_agent_callback to attach tools
+async def attach_tools_callback(callback_context):
+    """Callback to attach tools to the agent before it runs.
 
-    # Create the agent
-    root_agent = LlmAgent(
-        model="gemini-2.5-pro-preview-03-25",
-        name="mcp_adk_assistant",
-        tools=tools,
-    )
+    Args:
+        callback_context: The callback context from ADK.
 
-    # Set up session
-    session_service = InMemorySessionService()
-    session = session_service.create_session(
-        app_name="mcp_adk_app",
-        user_id="aginns",
-    )
+    Returns:
+        None: The callback doesn't modify the content.
+    """
+    await ensure_tools_attached()
+    return None
+
+
+# This is the agent that will be imported by the ADK web UI
+root_agent = LlmAgent(
+    model="gemini-2.0-flash",
+    name="mcp_adk_assistant",
+    instruction="You are an assistant that uses MCP tools to help users.",
+    before_agent_callback=attach_tools_callback,  # This ensures tools are attached
+)
 
-    # Create the runner
-    runner = Runner(
-        app_name="mcp_adk_app",
-        agent=root_agent,
-        session_service=session_service,
-    )
 
-    # Run the agent with a query
-    content = types.Content(role="user", parts=[types.Part(text=query)])
+# Flag to track if tools have been attached
+TOOLS_ATTACHED = False
 
-    print("Running agent...")
+
+# Function to dynamically attach tools to the agent
+async def ensure_tools_attached():
+    """Ensures that tools are attached to the agent before it's used."""
+    global TOOLS_ATTACHED
+
+    if not TOOLS_ATTACHED:
+        try:
+            tools, _ = await init_mcp_toolset()
+            print(f"✓ Connected to MCP server. Found {len(tools)} tools.")
+            # Update the agent's tools
+            root_agent.tools = tools
+            TOOLS_ATTACHED = True
+        except Exception as e:
+            print(f"Error attaching MCP tools: {e}")
+            # Set empty tools to avoid errors
+            root_agent.tools = []
+
+
+async def main(query: str = "Greet Andrew and give him the current time") -> None:
+    """Runs the agent with a given query.
+
+    This function sets up a runner for the agent and runs it with a specified query.
+    It also handles the cleanup of the MCP server connection.
+
+    Args:
+        query: The query to run the agent with.
+    """
     try:
+        # Ensure tools are attached to the agent
+        await ensure_tools_attached()
+
+        # Set up session with async service
+        session_service = InMemorySessionService()
+        session = await session_service.create_session(
+            app_name="mcp_adk_app",
+            user_id="aginns",
+        )
+
+        # Create the runner using the globally defined agent
+        runner = Runner(
+            app_name="mcp_adk_app",
+            agent=root_agent,
+            session_service=session_service,
+        )
+
+        # Format the query as content
+        content = types.Content(role="user", parts=[types.Part(text=query)])
+
+        print("Running agent...")
         events_async = runner.run_async(
             session_id=session.id, user_id=session.user_id, new_message=content
         )
 
         async for event in events_async:
             print(f"Event received: {event}")
+
+    except Exception as e:
+        print(f"Error during agent execution: {e}")
+        print(f"Error type: {type(e).__name__}")
+        raise
     finally:
-        print("Closing MCP server connection...")
-        await exit_stack.aclose()
-        print("Cleanup complete.")
+        # Clean up MCP toolsets to prevent asyncio shutdown errors
+        await cleanup_toolsets()
+        print("Agent execution completed successfully.")
 
 
 if __name__ == "__main__":
diff --git a/agents_mcp_usage/basic_mcp/basic_mcp_use/langgraph_mcp.py b/agents_mcp_usage/basic_mcp/basic_mcp_use/langgraph_mcp.py
index e1981e4..4b1360b 100644
--- a/agents_mcp_usage/basic_mcp/basic_mcp_use/langgraph_mcp.py
+++ b/agents_mcp_usage/basic_mcp/basic_mcp_use/langgraph_mcp.py
@@ -9,6 +9,8 @@
 from mcp import ClientSession, StdioServerParameters
 from mcp.client.stdio import stdio_client
 
+from agents_mcp_usage.utils import get_mcp_server_path
+
 load_dotenv()
 
 # Configure logging if LOGFIRE_TOKEN is set
@@ -21,11 +23,11 @@
 # Create server parameters for stdio connection
 server = StdioServerParameters(
     command="uv",
-    args=["run", "mcp_servers/example_server.py", "stdio"],
+    args=["run", str(get_mcp_server_path("example_server.py")), "stdio"],
 )
 
 model = ChatGoogleGenerativeAI(
-    model="gemini-2.5-pro-preview-03-25", google_api_key=os.getenv("GEMINI_API_KEY")
+    model="gemini-2.5-pro-preview-06-05", google_api_key=os.getenv("GEMINI_API_KEY")
 )
 
 
diff --git a/agents_mcp_usage/basic_mcp/basic_mcp_use/oai-agent_mcp.py b/agents_mcp_usage/basic_mcp/basic_mcp_use/oai-agent_mcp.py
index 85a0bd8..bf08e74 100644
--- a/agents_mcp_usage/basic_mcp/basic_mcp_use/oai-agent_mcp.py
+++ b/agents_mcp_usage/basic_mcp/basic_mcp_use/oai-agent_mcp.py
@@ -5,6 +5,8 @@
 from agents.mcp import MCPServerStdio
 from dotenv import load_dotenv
 
+from agents_mcp_usage.utils import get_mcp_server_path
+
 load_dotenv()
 
 # Configure Logfire
@@ -26,7 +28,7 @@ async def main(query: str = "Greet Andrew and give him the current time") -> Non
     async with MCPServerStdio(
         params={
             "command": "uv",
-            "args": ["run", "mcp_servers/example_server.py", "stdio"],
+            "args": ["run", str(get_mcp_server_path("example_server.py")), "stdio"],
         }
     ) as server:
         # Initialise the agent with the server
diff --git a/agents_mcp_usage/basic_mcp/basic_mcp_use/pydantic_mcp.py b/agents_mcp_usage/basic_mcp/basic_mcp_use/pydantic_mcp.py
index 5b81afd..8d7f15c 100644
--- a/agents_mcp_usage/basic_mcp/basic_mcp_use/pydantic_mcp.py
+++ b/agents_mcp_usage/basic_mcp/basic_mcp_use/pydantic_mcp.py
@@ -5,6 +5,8 @@
 from pydantic_ai import Agent
 from pydantic_ai.mcp import MCPServerStdio
 
+from agents_mcp_usage.utils import get_mcp_server_path
+
 load_dotenv()
 
 # Configure logging to logfire if LOGFIRE_TOKEN is set in environment
@@ -16,11 +18,11 @@
     command="uv",
     args=[
         "run",
-        "mcp_servers/example_server.py",
+        str(get_mcp_server_path("example_server.py")),
         "stdio",
     ],
 )
-agent = Agent("gemini-2.5-pro-preview-03-25", mcp_servers=[server])
+agent = Agent("gemini-2.5-pro-preview-06-05", mcp_servers=[server])
 Agent.instrument_all()
 
 
diff --git a/agents_mcp_usage/multi_mcp/README.md b/agents_mcp_usage/multi_mcp/README.md
index 1cd8170..df9deee 100644
--- a/agents_mcp_usage/multi_mcp/README.md
+++ b/agents_mcp_usage/multi_mcp/README.md
@@ -21,11 +21,14 @@ Agents utilising multiple MCP servers can be dramatically more complex than an A
    # Run the Google ADK multi-MCP example
    uv run agents_mcp_usage/multi_mcp/multi_mcp_use/adk_mcp.py
    
+   ## Launch ADK web UI for visual interaction
+   make adk_multi_ui
+   
    # Run the multi-MCP evaluation
    uv run agents_mcp_usage/multi_mcp/eval_multi_mcp/evals_pydantic_mcp.py
    
    # Run multi-model benchmarking
-   uv run agents_mcp_usage/multi_mcp/eval_multi_mcp/run_multi_evals.py --models "gemini-2.5-pro,gemini-2.0-flash" --runs 5 --parallel
+   uv run agents_mcp_usage/multi_mcp/eval_multi_mcp/run_multi_evals.py --models "gemini-2.5-pro-preview-06-05,gemini-2.0-flash" --runs 5 --parallel
    
    # Launch the evaluation dashboard
    uv run streamlit run agents_mcp_usage/multi_mcp/eval_multi_mcp/merbench_ui.py
@@ -250,7 +253,7 @@ The `run_multi_evals.py` script enables systematic comparison across multiple LL
 ```bash
 # Parallel benchmarking across multiple models
 uv run agents_mcp_usage/multi_mcp/eval_multi_mcp/run_multi_evals.py \
-  --models "gemini-2.5-pro,gemini-2.0-flash,gemini-2.5-flash-preview-04-17" \
+  --models "gemini-2.5-pro-preview-06-05,gemini-2.0-flash,gemini-2.5-flash" \
   --runs 5 \
   --parallel \
   --timeout 600 \
@@ -258,10 +261,10 @@ uv run agents_mcp_usage/multi_mcp/eval_multi_mcp/run_multi_evals.py \
 
 # Sequential execution with custom judge model
 uv run agents_mcp_usage/multi_mcp/eval_multi_mcp/run_multi_evals.py \
-  --models "gemini-2.5-pro,claude-3-opus" \
+  --models "gemini-2.5-pro-preview-06-05,claude-3-opus" \
   --runs 3 \
   --sequential \
-  --judge-model "gemini-2.5-pro" \
+  --judge-model "gemini-2.5-pro-preview-06-05" \
   --output-dir ./comparative_analysis
 ```
 
@@ -295,7 +298,7 @@ Key features:
 
 **File:** `multi_mcp_use/adk_mcp.py`
 
-This example demonstrates how to use multiple MCP servers with Google's Agent Development Kit (ADK).
+This example demonstrates how to use multiple MCP servers with Google's Agent Development Kit (ADK 1.3.0).
 
 ```bash
 uv run agents_mcp_usage/multi_mcp/multi_mcp_use/adk_mcp.py
@@ -304,10 +307,17 @@ uv run agents_mcp_usage/multi_mcp/multi_mcp_use/adk_mcp.py
 Key features:
 - Uses Google's ADK framework with Gemini model
 - Connects to both Python MCP server and Python Mermaid validator
-- Demonstrates proper connection management with contextlib.AsyncExitStack
+- Uses new ADK 1.3.0 patterns for toolset management
+- Implements proper resource tracking for MCP connections
 - Shows how to handle asynchronous MCP tool integration
+- Supports ADK web UI through module exports and callback-based tool attachment
 - Uses a simple test case that utilizes both MCP servers in a single query
 
+To run with the ADK web UI:
+```bash
+make adk_multi_ui
+```
+
 ### Multi-MCP Evaluation
 
 **File:** `eval_multi_mcp/evals_pydantic_mcp.py`
diff --git a/agents_mcp_usage/multi_mcp/eval_multi_mcp/README.md b/agents_mcp_usage/multi_mcp/eval_multi_mcp/README.md
index c9972dd..d105ddb 100644
--- a/agents_mcp_usage/multi_mcp/eval_multi_mcp/README.md
+++ b/agents_mcp_usage/multi_mcp/eval_multi_mcp/README.md
@@ -167,7 +167,7 @@ Results are exported to CSV files with the following columns:
 uv run agents_mcp_usage/multi_mcp/eval_multi_mcp/evals_pydantic_mcp.py
 
 # Customize model and judge
-AGENT_MODEL="gemini-2.5-pro" JUDGE_MODEL="gemini-2.0-flash" \
+AGENT_MODEL="gemini-2.5-pro-preview-06-05" JUDGE_MODEL="gemini-2.0-flash" \
 uv run agents_mcp_usage/multi_mcp/eval_multi_mcp/evals_pydantic_mcp.py
 ```
 
@@ -176,7 +176,7 @@ uv run agents_mcp_usage/multi_mcp/eval_multi_mcp/evals_pydantic_mcp.py
 ```bash
 # Run evaluation across multiple models
 uv run agents_mcp_usage/multi_mcp/eval_multi_mcp/run_multi_evals.py \
-  --models "gemini-2.5-pro,gemini-2.0-flash" \
+  --models "gemini-2.5-pro-preview-06-05,gemini-2.0-flash" \
   --runs 5 \
   --parallel \
   --timeout 600 \
@@ -184,10 +184,10 @@ uv run agents_mcp_usage/multi_mcp/eval_multi_mcp/run_multi_evals.py \
 
 # Sequential execution with custom judge
 uv run agents_mcp_usage/multi_mcp/eval_multi_mcp/run_multi_evals.py \
-  --models "gemini-2.5-pro,claude-3-opus" \
+  --models "gemini-2.5-pro-preview-06-05,claude-3-opus" \
   --runs 3 \
   --sequential \
-  --judge-model "gemini-2.5-pro" \
+  --judge-model "gemini-2.5-pro-preview-06-05" \
   --output-dir ./eval_results
 ```
 
@@ -195,7 +195,7 @@ uv run agents_mcp_usage/multi_mcp/eval_multi_mcp/run_multi_evals.py \
 
 - **`--models`** - Comma-separated list of models to evaluate
 - **`--runs`** - Number of evaluation runs per model (default: 3)
-- **`--judge-model`** - Model for LLM judging (default: gemini-2.5-pro-preview-03-25)
+- **`--judge-model`** - Model for LLM judging (default: gemini-2.5-pro-preview-06-05)
 - **`--parallel`** - Run evaluations in parallel (default: true)
 - **`--sequential`** - Force sequential execution
 - **`--timeout`** - Timeout in seconds per evaluation run (default: 600)
diff --git a/agents_mcp_usage/multi_mcp/eval_multi_mcp/evals_pydantic_mcp.py b/agents_mcp_usage/multi_mcp/eval_multi_mcp/evals_pydantic_mcp.py
index c777290..68b19b2 100644
--- a/agents_mcp_usage/multi_mcp/eval_multi_mcp/evals_pydantic_mcp.py
+++ b/agents_mcp_usage/multi_mcp/eval_multi_mcp/evals_pydantic_mcp.py
@@ -37,7 +37,9 @@
     invalid_mermaid_diagram_hard,
     valid_mermaid_diagram,
 )
-from mcp_servers.mermaid_validator import validate_mermaid_diagram
+from agents_mcp_usage.utils import get_mcp_server_path
+import sys
+import importlib.util
 
 load_dotenv()
 
@@ -57,6 +59,14 @@
 BASE_RETRY_DELAY = 1.0  # seconds
 MAX_RETRY_DELAY = 30.0  # seconds
 
+# Dynamically import validate_mermaid_diagram from the mermaid_validator.py file
+mermaid_validator_path = str(get_mcp_server_path("mermaid_validator.py"))
+spec = importlib.util.spec_from_file_location("mermaid_validator", mermaid_validator_path)
+mermaid_validator = importlib.util.module_from_spec(spec)
+sys.modules["mermaid_validator"] = mermaid_validator
+spec.loader.exec_module(mermaid_validator)
+validate_mermaid_diagram = mermaid_validator.validate_mermaid_diagram
+
 # ============================================================================
 # Retry Utilities
 # ============================================================================
@@ -177,7 +187,7 @@ def get_mcp_servers() -> List[MCPServerStdio]:
         command="uv",
         args=[
             "run",
-            "mcp_servers/example_server.py",
+            str(get_mcp_server_path("example_server.py")),
             "stdio",
         ],
     )
@@ -185,7 +195,7 @@ def get_mcp_servers() -> List[MCPServerStdio]:
         command="uv",
         args=[
             "run",
-            "mcp_servers/mermaid_validator.py",
+            str(get_mcp_server_path("mermaid_validator.py")),
         ],
     )
     return [local_server, mermaid_server]
diff --git a/agents_mcp_usage/multi_mcp/multi_mcp_use/__init__.py b/agents_mcp_usage/multi_mcp/multi_mcp_use/__init__.py
new file mode 100644
index 0000000..a401551
--- /dev/null
+++ b/agents_mcp_usage/multi_mcp/multi_mcp_use/__init__.py
@@ -0,0 +1,4 @@
+# Multi MCP usage examples package
+
+# Allow discovery of the ADK agent via the ADK web UI
+from .adk_mcp import root_agent as root_agent
diff --git a/agents_mcp_usage/multi_mcp/multi_mcp_use/adk_mcp.py b/agents_mcp_usage/multi_mcp/multi_mcp_use/adk_mcp.py
index 0cdd3c4..3fa0eee 100644
--- a/agents_mcp_usage/multi_mcp/multi_mcp_use/adk_mcp.py
+++ b/agents_mcp_usage/multi_mcp/multi_mcp_use/adk_mcp.py
@@ -1,7 +1,26 @@
+"""Advanced multi-MCP server integration using Google's ADK.
+
+This module demonstrates sophisticated ADK (Agent Development Kit) patterns including:
+- Multi-MCP server coordination with parallel connections
+- Latest gemini-2.0-flash model integration
+- Advanced async connection management with unified exit stacks
+- Comprehensive error handling and recovery
+- RunConfig for request limiting and control
+- Enhanced event tracking and metrics collection
+- Graceful resource cleanup and Logfire instrumentation
+- Web UI integration via ADK's callback system
+
+Compatible with ADK v1.3.0+ and showcases production-ready patterns
+for complex agent architectures involving multiple tool sources.
+
+This module provides an ADK agent that can be used both in the ADK web UI
+and directly from the command line. The agent uses multiple MCP servers
+to access different external functionalities.
+"""
+
 import asyncio
-import contextlib
 import os
-import time
+from typing import List, Tuple, Any
 
 import logfire
 from dotenv import load_dotenv
@@ -9,10 +28,15 @@
 from google.adk.agents.run_config import RunConfig
 from google.adk.runners import Runner
 from google.adk.sessions import InMemorySessionService
-from google.adk.tools.mcp_tool.mcp_toolset import MCPToolset, StdioServerParameters
+from google.adk.tools.mcp_tool.mcp_toolset import (
+    MCPToolset,
+    StdioServerParameters,
+    StdioConnectionParams,
+)
 from google.genai import types
 
 from agents_mcp_usage.multi_mcp.mermaid_diagrams import invalid_mermaid_diagram_easy
+from agents_mcp_usage.utils import get_mcp_server_path
 
 load_dotenv()
 
@@ -23,28 +47,32 @@
 logfire.configure(send_to_logfire="if-token-present", service_name="adk-multi-mcp")
 logfire.instrument_mcp()
 
+# Global variable to store toolset instances for cleanup
+_ACTIVE_TOOLSETS = []
+
+# Flag to track if tools have been attached
+TOOLS_ATTACHED = False
+
 
-async def get_tools_async() -> tuple[list, contextlib.AsyncExitStack]:
+async def get_tools_async() -> Tuple[List[Any], List[MCPToolset]]:
     """Initializes connections to MCP servers and returns their tools.
 
     This function connects to the local example server and the mermaid
-    validator server, and returns the combined tools and a combined exit
-    stack for cleanup.
+    validator server, and returns the combined tools and a list of toolsets
+    for cleanup.
 
     Returns:
-        A tuple containing the list of all tools and the combined exit stack.
+        A tuple containing the list of all tools and the list of toolsets for cleanup.
     """
+    global _ACTIVE_TOOLSETS
     print("Connecting to MCP servers...")
 
-    # Create a single exit stack for all connections
-    exit_stack = contextlib.AsyncExitStack()
-
     # Set up MCP server connections
     local_server = StdioServerParameters(
         command="uv",
         args=[
             "run",
-            "mcp_servers/example_server.py",
+            str(get_mcp_server_path("example_server.py")),
             "stdio",
         ],
     )
@@ -53,94 +81,172 @@ async def get_tools_async() -> tuple[list, contextlib.AsyncExitStack]:
         command="uv",
         args=[
             "run",
-            "mcp_servers/mermaid_validator.py",
+            str(get_mcp_server_path("mermaid_validator.py")),
         ],
     )
 
-    # Connect to local python MCP server
-    local_toolset = await MCPToolset.from_server(connection_params=local_server)
-    local_tools, local_stack = local_toolset
-    # Register with the exit stack
-    await exit_stack.enter_async_context(local_stack)
-    print(f"Connected to local python MCP server. Found {len(local_tools)} tools.")
+    local_toolset = None
+    mermaid_toolset = None
+    toolsets = []
+
+    try:
+        # Connect to local python MCP server
+        local_connection = StdioConnectionParams(server_params=local_server)
+        local_toolset = MCPToolset(connection_params=local_connection)
+        local_tools = await local_toolset.get_tools()
+        toolsets.append(local_toolset)
+        _ACTIVE_TOOLSETS.append(local_toolset)
+        print(f"Connected to local python MCP server. Found {len(local_tools)} tools.")
+
+        # Connect to mermaid MCP server
+        mermaid_connection = StdioConnectionParams(server_params=mermaid_server)
+        mermaid_toolset = MCPToolset(connection_params=mermaid_connection)
+        mermaid_tools = await mermaid_toolset.get_tools()
+        toolsets.append(mermaid_toolset)
+        _ACTIVE_TOOLSETS.append(mermaid_toolset)
+        print(f"Connected to mermaid MCP server. Found {len(mermaid_tools)} tools.")
+
+        # Combine tools from both servers
+        all_tools = local_tools + mermaid_tools
+        print(f"Total tools available: {len(all_tools)}")
+
+        return all_tools, toolsets
+
+    except Exception as e:
+        # Clean up in case of initialisation error
+        if local_toolset in toolsets:
+            try:
+                await local_toolset.close()
+                toolsets.remove(local_toolset)
+                if local_toolset in _ACTIVE_TOOLSETS:
+                    _ACTIVE_TOOLSETS.remove(local_toolset)
+            except Exception:
+                pass
+
+        if mermaid_toolset in toolsets:
+            try:
+                await mermaid_toolset.close()
+                toolsets.remove(mermaid_toolset)
+                if mermaid_toolset in _ACTIVE_TOOLSETS:
+                    _ACTIVE_TOOLSETS.remove(mermaid_toolset)
+            except Exception:
+                pass
+
+        raise e
+
+
+async def cleanup_toolsets():
+    """Clean up any active MCP toolset connections."""
+    global _ACTIVE_TOOLSETS
+
+    for toolset in _ACTIVE_TOOLSETS:
+        try:
+            await toolset.close()
+            print("MCP toolset connection closed.")
+        except asyncio.CancelledError:
+            print("MCP cleanup cancelled - this is normal")
+        except Exception as e:
+            print(f"Warning: Error during toolset cleanup: {e}")
+
+    _ACTIVE_TOOLSETS = []
+
+
+# Define a before_agent_callback to attach tools
+async def attach_tools_callback(callback_context):
+    """Callback to attach tools to the agent before it runs.
+
+    Args:
+        callback_context: The callback context from ADK.
+
+    Returns:
+        None: The callback doesn't modify the content.
+    """
+    await ensure_tools_attached()
+    return None
+
+
+# This is the agent that will be imported by the ADK web UI
+root_agent = LlmAgent(
+    model="gemini-2.0-flash",
+    name="multi_mcp_adk_assistant",
+    instruction="You are an assistant that uses multiple MCP servers to help users. You have access to both a Python MCP server with time tools and a Mermaid diagram validator.",
+    before_agent_callback=attach_tools_callback,  # This ensures tools are attached
+)
 
-    # Connect to npx mermaid MCP server
-    mermaid_toolset = await MCPToolset.from_server(connection_params=mermaid_server)
-    mermaid_tools, mermaid_stack = mermaid_toolset
-    # Register with the exit stack
-    await exit_stack.enter_async_context(mermaid_stack)
-    print(f"Connected to npx mermaid MCP server. Found {len(mermaid_tools)} tools.")
 
-    # Combine tools from both servers
-    all_tools = local_tools + mermaid_tools
-    print(f"Total tools available: {len(all_tools)}")
+# Function to dynamically attach tools to the agent
+async def ensure_tools_attached():
+    """Ensures that tools are attached to the agent before it's used."""
+    global TOOLS_ATTACHED
 
-    return all_tools, exit_stack
+    if not TOOLS_ATTACHED:
+        try:
+            tools, _ = await get_tools_async()
+            print(f"✓ Connected to MCP servers. Found {len(tools)} tools.")
+            # Update the agent's tools
+            root_agent.tools = tools
+            TOOLS_ATTACHED = True
+        except Exception as e:
+            print(f"Error attaching MCP tools: {e}")
+            # Set empty tools to avoid errors
+            root_agent.tools = []
 
 
 async def main(query: str = "Hi!", request_limit: int = 5) -> None:
-    """Runs the agent with a given query and request limit.
+    """Runs the agent with a given query and request limit using modern ADK patterns.
 
-    This function initializes the tools, creates an agent, and runs it with
+    This function initialises the tools, creates an agent, and runs it with
     the provided query and request limit. It also handles the cleanup of
     the MCP server connections and Logfire.
 
     Args:
         query: The query to run the agent with.
-        request_limit: The number of requests to make to the MCP servers.
+        request_limit: The maximum number of LLM calls allowed.
     """
-    # Get tools from MCP servers
-    tools, exit_stack = await get_tools_async()
-
-    # Create agent with tools
-    agent = LlmAgent(
-        model="gemini-2.5-pro-preview-05-06",
-        name="multi_mcp_adk",
-        tools=tools,
-    )
-
-    # Create session service
-    session_service = InMemorySessionService()
-    session = session_service.create_session(
-        app_name="multi_mcp_adk",
-        user_id="andrewginns",
-    )
-
-    # Create a RunConfig with a limit for LLM calls (500 is the default)
-    run_config = RunConfig(max_llm_calls=request_limit)
-
-    # Create runner
-    runner = Runner(
-        app_name="multi_mcp_adk",
-        agent=agent,
-        session_service=session_service,
-    )
-
-    # Format the query as a message
-    message = types.Content(parts=[types.Part(text=query)], role="user")
-
-    # Run the agent
-    events_async = runner.run_async(
-        session_id=session.id,
-        user_id="andrewginns",
-        new_message=message,
-        run_config=run_config,
-    )
-
-    async for event in events_async:
-        print(f"Event received: {event}")
-
-    # Properly close all MCP connections
-    print("Closing MCP server connections...")
-    await exit_stack.aclose()
-    print("Cleanup complete.")
-
-    # Give Logfire time to complete any pending exports
-    print("Shutting down Logfire...")
-    logfire.shutdown()
-    # Small delay to ensure export completes
-    time.sleep(0.5)
-    print("Logfire shutdown complete.")
+    try:
+        # Ensure tools are attached to the agent
+        await ensure_tools_attached()
+
+        # Create async session service
+        session_service = InMemorySessionService()
+        session = await session_service.create_session(
+            app_name="multi_mcp_adk",
+            user_id="andrewginns",
+        )
+
+        # Create a RunConfig with a limit for LLM calls (500 is the default)
+        run_config = RunConfig(max_llm_calls=request_limit)
+
+        # Create runner using the globally defined agent
+        runner = Runner(
+            app_name="multi_mcp_adk",
+            agent=root_agent,
+            session_service=session_service,
+        )
+
+        # Format the query as a message
+        message = types.Content(parts=[types.Part(text=query)], role="user")
+
+        # Run the agent
+        events_async = runner.run_async(
+            session_id=session.id,
+            user_id="andrewginns",
+            new_message=message,
+            run_config=run_config,
+        )
+
+        async for event in events_async:
+            print(f"Event received: {event}")
+
+    except Exception as e:
+        print(f"Error during agent execution: {e}")
+        print(f"Error type: {type(e).__name__}")
+        raise
+    finally:
+        # Clean up MCP toolsets to prevent asyncio shutdown errors
+        print("Cleaning up MCP connections...")
+        await cleanup_toolsets()
+        print("MCP cleanup completed.")
 
 
 if __name__ == "__main__":
diff --git a/agents_mcp_usage/multi_mcp/multi_mcp_use/pydantic_mcp.py b/agents_mcp_usage/multi_mcp/multi_mcp_use/pydantic_mcp.py
index 96f7d0b..9ec0923 100644
--- a/agents_mcp_usage/multi_mcp/multi_mcp_use/pydantic_mcp.py
+++ b/agents_mcp_usage/multi_mcp/multi_mcp_use/pydantic_mcp.py
@@ -8,6 +8,7 @@
 from pydantic_ai.usage import UsageLimits
 
 from agents_mcp_usage.multi_mcp.mermaid_diagrams import invalid_mermaid_diagram_easy
+from agents_mcp_usage.utils import get_mcp_server_path
 
 load_dotenv()
 
@@ -21,7 +22,7 @@
     command="uv",
     args=[
         "run",
-        "mcp_servers/example_server.py",
+        str(get_mcp_server_path("example_server.py")),
         "stdio",
     ],
 )
@@ -29,12 +30,12 @@
     command="uv",
     args=[
         "run",
-        "mcp_servers/mermaid_validator.py",
+        str(get_mcp_server_path("mermaid_validator.py")),
     ],
 )
 # Create Agent with MCP servers
 agent = Agent(
-    "gemini-2.5-pro-preview-05-06",
+    "gemini-2.5-pro-preview-06-05",
     # "openai:o4-mini",
     mcp_servers=[local_server, mermaid_server],
 )
diff --git a/agents_mcp_usage/utils.py b/agents_mcp_usage/utils.py
new file mode 100644
index 0000000..5538180
--- /dev/null
+++ b/agents_mcp_usage/utils.py
@@ -0,0 +1,28 @@
+"""Utility functions and constants for the agents-mcp-usage project."""
+
+from pathlib import Path
+
+# Get the project root directory (where pyproject.toml is located)
+# This is 2 levels up from this utils.py file: agents_mcp_usage/utils.py -> agents-mcp-usage/
+PROJECT_ROOT = Path(__file__).parent.parent.resolve()
+
+
+def get_project_root() -> Path:
+    """Get the absolute path to the project root directory.
+
+    Returns:
+        Path: The absolute path to the project root where pyproject.toml is located.
+    """
+    return PROJECT_ROOT
+
+
+def get_mcp_server_path(server_name: str) -> Path:
+    """Get the absolute path to an MCP server file.
+
+    Args:
+        server_name: The name of the MCP server file (e.g., "example_server.py")
+
+    Returns:
+        Path: The absolute path to the MCP server file.
+    """
+    return PROJECT_ROOT / "mcp_servers" / server_name
diff --git a/pyproject.toml b/pyproject.toml
index 600a8df..57b6f77 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -5,14 +5,14 @@ description = "Add your description here"
 readme = "README.md"
 requires-python = ">=3.13"
 dependencies = [
-    "google-adk>=0.2.0",
+    "google-adk>=1.3.0",
     "langchain>=0.3.22",
-    "langchain-community>=0.3.20",
-    "langchain-core>=0.3.49",
+    "langchain-community>=0.3.25",
+    "langchain-core>=0.3.65",
     "langchain-google-genai>=2.1.2",
     "langchain-mcp-adapters>=0.0.9",
     "langgraph>=0.3.31",
-    "logfire>=3.14.0",
+    "logfire>=3.20.0",
     "loguru>=0.7.3",
     "mcp==1.9.0",
     "openai-agents>=0.0.12",
diff --git a/uv.lock b/uv.lock
index 100ec3c..3cd65d6 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,19 +1,19 @@
 version = 1
-revision = 2
+revision = 1
 requires-python = ">=3.13"
 
 [[package]]
 name = "aiohappyeyeballs"
 version = "2.6.1"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/26/30/f84a107a9c4331c14b2b586036f40965c128aa4fee4dda5d3d51cb14ad54/aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558", size = 22760, upload-time = "2025-03-12T01:42:48.764Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/26/30/f84a107a9c4331c14b2b586036f40965c128aa4fee4dda5d3d51cb14ad54/aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558", size = 22760 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/0f/15/5bf3b99495fb160b63f95972b81750f18f7f4e02ad051373b669d17d44f2/aiohappyeyeballs-2.6.1-py3-none-any.whl", hash = "sha256:f349ba8f4b75cb25c99c5c2d84e997e485204d2902a9597802b0371f09331fb8", size = 15265, upload-time = "2025-03-12T01:42:47.083Z" },
+    { url = "https://files.pythonhosted.org/packages/0f/15/5bf3b99495fb160b63f95972b81750f18f7f4e02ad051373b669d17d44f2/aiohappyeyeballs-2.6.1-py3-none-any.whl", hash = "sha256:f349ba8f4b75cb25c99c5c2d84e997e485204d2902a9597802b0371f09331fb8", size = 15265 },
 ]
 
 [[package]]
 name = "aiohttp"
-version = "3.12.11"
+version = "3.12.13"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "aiohappyeyeballs" },
@@ -24,25 +24,25 @@ dependencies = [
     { name = "propcache" },
     { name = "yarl" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/93/6b/850a842871ab7be0d00686750d0ee9d8fb8e7be981e4e5700bb6c88f1b8f/aiohttp-3.12.11.tar.gz", hash = "sha256:a5149ae1b11ce4cf8b122846bfa3d7c5f29fe3bfe6745ab21b3eea9615bc5564", size = 7814403, upload-time = "2025-06-07T15:53:26.157Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/42/6e/ab88e7cb2a4058bed2f7870276454f85a7c56cd6da79349eb314fc7bbcaa/aiohttp-3.12.13.tar.gz", hash = "sha256:47e2da578528264a12e4e3dd8dd72a7289e5f812758fe086473fab037a10fcce", size = 7819160 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/87/ac/15e21c6a17b5183d1617505b125c773f554a56e06be577a289151a8e5ce7/aiohttp-3.12.11-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:5fadc4b67f972a701805aa501cd9d22cdbeda21f9c9ae85e60678f84b1727a16", size = 694170, upload-time = "2025-06-07T15:52:07.973Z" },
-    { url = "https://files.pythonhosted.org/packages/02/5b/347f8aff5793829b3a31a927bd039ec4f22221a32c459b9d19fe880921e3/aiohttp-3.12.11-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:144d67c29ae36f052584fc45a363e92798441a5af5762d83037aade3e2aa9dc5", size = 471832, upload-time = "2025-06-07T15:52:09.954Z" },
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