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adk-python/contributing/samples/mcp_progress_callback_agent/agent.py
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# Copyright 2026 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Sample agent demonstrating MCP progress callback feature.
This sample shows how to use the progress_callback parameter in McpToolset
to receive progress notifications from MCP servers during long-running tool
executions.
There are two ways to use progress callbacks:
1. Simple callback (shared by all tools):
Pass a ProgressFnT callback that receives (progress, total, message).
2. Factory function (per-tool callbacks with runtime context):
Pass a ProgressCallbackFactory that takes (tool_name, callback_context, **kwargs)
and returns a ProgressFnT or None. This allows different tools to have different
progress handling logic, and the factory can access and modify session state
via the CallbackContext. The **kwargs ensures forward compatibility for future
parameters.
IMPORTANT: Progress callbacks only work when the MCP server actually sends
progress notifications. Most simple MCP servers (like the filesystem server)
do not send progress updates. This sample uses a mock server that demonstrates
progress reporting.
Usage:
adk run contributing/samples/mcp_progress_callback_agent
Then try:
"Run the long running task with 5 steps"
"Process these items: apple, banana, cherry"
"""
import os
import sys
from typing import Any
from google.adk.agents.callback_context import CallbackContext
from google.adk.agents.llm_agent import LlmAgent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool import StdioConnectionParams
from mcp import StdioServerParameters
from mcp.shared.session import ProgressFnT
_current_dir = os.path.dirname(os.path.abspath(__file__))
_mock_server_path = os.path.join(_current_dir, "mock_progress_server.py")
# Option 1: Simple shared callback
async def simple_progress_callback(
progress: float,
total: float | None,
message: str | None,
) -> None:
"""Handle progress notifications from MCP server.
This callback is shared by all tools in the toolset.
"""
if total is not None:
percentage = (progress / total) * 100
bar_length = 20
filled = int(bar_length * progress / total)
bar = "=" * filled + "-" * (bar_length - filled)
print(f"[{bar}] {percentage:.0f}% ({progress}/{total}) {message or ''}")
else:
print(f"Progress: {progress} {f'- {message}' if message else ''}")
# Option 2: Factory function for per-tool callbacks with runtime context
def progress_callback_factory(
tool_name: str,
*,
callback_context: CallbackContext | None = None,
**kwargs: Any,
) -> ProgressFnT | None:
"""Create a progress callback for a specific tool.
This factory allows different tools to have different progress handling.
It receives a CallbackContext for accessing and modifying runtime information
like session state. The **kwargs parameter ensures forward compatibility.
Args:
tool_name: The name of the MCP tool.
callback_context: The callback context providing access to session,
state, artifacts, and other runtime information. Allows modifying
state via ctx.state['key'] = value. May be None if not available.
**kwargs: Additional keyword arguments for future extensibility.
Returns:
A progress callback function, or None if no callback is needed.
"""
# Example: Access session info from context (if available)
session_id = "unknown"
if callback_context and callback_context.session:
session_id = callback_context.session.id
async def callback(
progress: float,
total: float | None,
message: str | None,
) -> None:
# Include tool name and session info in the progress output
prefix = f"[{tool_name}][session:{session_id}]"
if total is not None:
percentage = (progress / total) * 100
bar_length = 20
filled = int(bar_length * progress / total)
bar = "=" * filled + "-" * (bar_length - filled)
print(f"{prefix} [{bar}] {percentage:.0f}% {message or ''}")
# Example: Store progress in state (callback_context allows modification)
if callback_context:
callback_context.state["last_progress"] = progress
callback_context.state["last_total"] = total
else:
print(
f"{prefix} Progress: {progress} {f'- {message}' if message else ''}"
)
return callback
root_agent = LlmAgent(
model="gemini-2.5-flash",
name="progress_demo_agent",
instruction="""\
You are a helpful assistant that can run long-running tasks.
Available tools:
- long_running_task: Simulates a task with multiple steps. You can specify
the number of steps and delay between them.
- process_items: Processes a list of items one by one with progress updates.
When the user asks you to run a task, use these tools and the progress
will be logged automatically.
Example requests:
- "Run a long task with 5 steps"
- "Process these items: apple, banana, cherry, date"
""",
tools=[
McpToolset(
connection_params=StdioConnectionParams(
server_params=StdioServerParameters(
command=sys.executable, # Use current Python interpreter
args=[_mock_server_path],
),
timeout=60,
),
# Use factory function for per-tool callbacks (Option 2)
# Or use simple_progress_callback for shared callback (Option 1)
progress_callback=progress_callback_factory,
)
],
)