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| Author | SHA1 | Date | |
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| 9ae753b5a4 | |||
| 082675546f | |||
| aa77834e2e |
@@ -65,8 +65,9 @@ async def check_prime(nums: list[int]) -> str:
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root_agent = Agent(
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# model='gemini-2.0-flash-live-preview-04-09', # for Vertex project
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model='gemini-2.0-flash-live-001', # for AI studio key
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model='gemini-live-2.5-flash-preview-native-audio-09-2025', # vertex
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# model='gemini-2.5-flash-native-audio-preview-09-2025', # for AI studio
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# key
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name='roll_dice_agent',
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description=(
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'hello world agent that can roll a dice of 6 sides and check prime'
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@@ -0,0 +1,70 @@
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# AgentTool with MCP Demo (SSE Mode)
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This demo shows how `AgentTool` works with MCP (Model Context Protocol) toolsets using **SSE mode**.
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## SSE vs Stdio Mode
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This demo uses **SSE (Server-Sent Events) mode** where the MCP server runs as a separate HTTP server:
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- **Remote connection** - Connects to server via HTTP
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- **Separate process** - Server must be started manually
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- **Network communication** - Uses HTTP/SSE for messaging
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For the **stdio (subprocess) version**, see [mcp_in_agent_tool_stdio](../mcp_in_agent_tool_stdio/).
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## Setup
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**Start the MCP simple-tool server in SSE mode** (in a separate terminal):
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```bash
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# Run the server using uvx (no installation needed)
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# Port 3000 avoids conflict with adk web (which uses 8000)
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uvx --from 'git+https://github.com/modelcontextprotocol/python-sdk.git#subdirectory=examples/servers/simple-tool' \
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mcp-simple-tool --transport sse --port 3000
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```
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The server should be accessible at `http://localhost:3000/sse`.
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## Running the Demo
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```bash
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adk web contributing/samples
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```
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Then select **mcp_in_agent_tool_remote** from the list and interact with the agent.
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## Try These Prompts
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This demo uses **Gemini 2.5 Flash** as the model. Try these prompts:
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1. **Check available tools:**
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```
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What tools do you have access to?
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```
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2. **Fetch and summarize JSON Schema specification:**
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```
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Use the mcp_helper to fetch https://json-schema.org/specification and summarize the key features of JSON Schema
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```
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## Architecture
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```
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main_agent (root_agent)
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│
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└── AgentTool wrapping:
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│
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└── mcp_helper (sub_agent)
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│
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└── McpToolset (SSE connection)
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│
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└── http://localhost:3000/sse
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│
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└── MCP simple-tool server
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│
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└── Website Fetcher Tool
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```
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## Related
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- **Issue:** [#1112 - Using agent as tool outside of adk web doesn't exit cleanly](https://github.com/google/adk-python/issues/1112)
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- **Related Issue:** [#929 - LiteLLM giving error with OpenAI models and Grafana's MCP server](https://github.com/google/adk-python/issues/929)
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- **Stdio Version:** [mcp_in_agent_tool_stdio](../mcp_in_agent_tool_stdio/) - Uses local subprocess connection
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@@ -0,0 +1,15 @@
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# Copyright 2025 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from . import agent
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@@ -0,0 +1,70 @@
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# Copyright 2025 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from google.adk.agents import Agent
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from google.adk.tools import AgentTool
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from google.adk.tools.mcp_tool import McpToolset
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from google.adk.tools.mcp_tool.mcp_session_manager import SseConnectionParams
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# Create MCP toolset
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# This uses the simple-tool MCP server via SSE
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# You need to start the MCP server separately (see README.md)
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mcp_toolset = McpToolset(
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connection_params=SseConnectionParams(
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url="http://localhost:3000/sse",
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timeout=10.0,
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sse_read_timeout=300.0,
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)
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)
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# Create sub-agent with MCP tools
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# This agent has direct access to MCP tools
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sub_agent = Agent(
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name="mcp_helper",
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model="gemini-2.5-flash",
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description=(
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"A helpful assistant with access to MCP tools for fetching websites."
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),
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instruction="""You are a helpful assistant with access to MCP tools.
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When the user asks for help:
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1. Explain what tools you have available (website fetching)
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2. Use the appropriate tool if needed
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3. Provide clear and helpful responses
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You have access to a website fetcher tool via MCP. Use it to fetch and return website content.""",
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tools=[mcp_toolset],
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)
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# Wrap sub-agent as an AgentTool
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# This allows the main agent to delegate tasks to the sub-agent
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# The sub-agent has access to MCP tools for fetching websites
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mcp_agent_tool = AgentTool(agent=sub_agent)
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# Create main agent
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# This agent can delegate to the sub-agent via AgentTool
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root_agent = Agent(
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name="main_agent",
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model="gemini-2.5-flash",
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description="Main agent that can delegate to a sub-agent with MCP tools.",
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instruction="""You are a helpful assistant. You have access to a sub-agent (mcp_helper)
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that has MCP tools for fetching websites.
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When the user asks for help:
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- If they need to fetch a website, call the mcp_helper tool
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- Otherwise, respond directly
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Always be helpful and explain what you're doing.""",
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tools=[mcp_agent_tool],
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)
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@@ -0,0 +1,70 @@
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# AgentTool with MCP Demo (Stdio Mode)
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This demo shows how `AgentTool` works with MCP (Model Context Protocol) toolsets using **stdio mode**.
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## Stdio vs SSE Mode
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This demo uses **stdio mode** where the MCP server runs as a subprocess:
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- **Simpler setup** - No need to start a separate server
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- **Auto-launched** - Server starts automatically when agent runs
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- **Local process** - Uses stdin/stdout for communication
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For the **SSE (remote server) version**, see [mcp_in_agent_tool_remote](../mcp_in_agent_tool_remote/).
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## Setup
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**No installation required!** The MCP server will be launched automatically using `uvx` when you run the agent.
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The demo uses `uvx` to fetch and run the MCP simple-tool server directly from the GitHub repository's subdirectory:
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```bash
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uvx --from 'git+https://github.com/modelcontextprotocol/python-sdk.git#subdirectory=examples/servers/simple-tool' \
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mcp-simple-tool
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```
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This happens automatically via the stdio connection when the agent starts.
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## Running the Demo
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```bash
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adk web contributing/samples
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```
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Then select **mcp_in_agent_tool_stdio** from the list and interact with the agent.
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## Try These Prompts
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||||
|
||||
This demo uses **Gemini 2.5 Flash** as the model. Try these prompts:
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||||
|
||||
1. **Check available tools:**
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```
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||||
What tools do you have access to?
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||||
```
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2. **Fetch and summarize JSON Schema specification:**
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```
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Use the mcp_helper to fetch https://json-schema.org/specification and summarize the key features of JSON Schema
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```
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## Architecture
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||||
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||||
```
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||||
main_agent (root_agent)
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||||
│
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└── AgentTool wrapping:
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│
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└── mcp_helper (sub_agent)
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│
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└── McpToolset (stdio connection)
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│
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└── MCP Server (subprocess via uvx)
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│
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└── uvx --from git+...#subdirectory=... mcp-simple-tool
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│
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└── Website Fetcher Tool
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```
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## Related
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- **Issue:** [#1112 - Using agent as tool outside of adk web doesn't exit cleanly](https://github.com/google/adk-python/issues/1112)
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- **Related Issue:** [#929 - LiteLLM giving error with OpenAI models and Grafana's MCP server](https://github.com/google/adk-python/issues/929)
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- **SSE Version:** [mcp_in_agent_tool_remote](../mcp_in_agent_tool_remote/) - Uses remote server connection
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@@ -0,0 +1,15 @@
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# Copyright 2025 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
|
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from . import agent
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@@ -0,0 +1,77 @@
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# Copyright 2025 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from google.adk.agents import Agent
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from google.adk.tools import AgentTool
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from google.adk.tools.mcp_tool import McpToolset
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from google.adk.tools.mcp_tool.mcp_session_manager import StdioConnectionParams
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from mcp import StdioServerParameters
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# Create MCP toolset
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# This uses the simple-tool MCP server via stdio
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# The server will be launched automatically using uvx from the subdirectory
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mcp_toolset = McpToolset(
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connection_params=StdioConnectionParams(
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server_params=StdioServerParameters(
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command="uvx",
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args=[
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"--from",
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"git+https://github.com/modelcontextprotocol/python-sdk.git#subdirectory=examples/servers/simple-tool",
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"mcp-simple-tool",
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],
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),
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timeout=10.0,
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)
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)
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# Create sub-agent with MCP tools
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# This agent has direct access to MCP tools
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sub_agent = Agent(
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name="mcp_helper",
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model="gemini-2.5-flash",
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description=(
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"A helpful assistant with access to MCP tools for fetching websites."
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),
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instruction="""You are a helpful assistant with access to MCP tools.
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|
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When the user asks for help:
|
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1. Explain what tools you have available (website fetching)
|
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2. Use the appropriate tool if needed
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3. Provide clear and helpful responses
|
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|
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You have access to a website fetcher tool via MCP. Use it to fetch and return website content.""",
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tools=[mcp_toolset],
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)
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# Wrap sub-agent as an AgentTool
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# This allows the main agent to delegate tasks to the sub-agent
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# The sub-agent has access to MCP tools for fetching websites
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mcp_agent_tool = AgentTool(agent=sub_agent)
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# Create main agent
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# This agent can delegate to the sub-agent via AgentTool
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root_agent = Agent(
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name="main_agent",
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model="gemini-2.5-flash",
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description="Main agent that can delegate to a sub-agent with MCP tools.",
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instruction="""You are a helpful assistant. You have access to a sub-agent (mcp_helper)
|
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that has MCP tools for fetching websites.
|
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|
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When the user asks for help:
|
||||
- If they need to fetch a website, call the mcp_helper tool
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- Otherwise, respond directly
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||||
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Always be helpful and explain what you're doing.""",
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tools=[mcp_agent_tool],
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)
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@@ -105,13 +105,14 @@ class GeminiLlmConnection(BaseLlmConnection):
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"""
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if isinstance(input, types.Blob):
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input_blob = input.model_dump()
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logger.debug('Sending LLM Blob: %s', input_blob)
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# The blob is binary and is very large. So let's not log it.
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logger.debug('Sending LLM Blob.')
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await self._gemini_session.send(input=input_blob)
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elif isinstance(input, types.ActivityStart):
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logger.debug('Sending LLM activity start signal')
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logger.debug('Sending LLM activity start signal.')
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await self._gemini_session.send_realtime_input(activity_start=input)
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elif isinstance(input, types.ActivityEnd):
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logger.debug('Sending LLM activity end signal')
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logger.debug('Sending LLM activity end signal.')
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await self._gemini_session.send_realtime_input(activity_end=input)
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else:
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raise ValueError('Unsupported input type: %s' % type(input))
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@@ -164,6 +164,10 @@ class AgentTool(BaseTool):
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if event.content:
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last_content = event.content
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# Clean up runner resources (especially MCP sessions)
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# to avoid "Attempted to exit cancel scope in a different task" errors
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await runner.close()
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if not last_content:
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return ''
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merged_text = '\n'.join(p.text for p in last_content.parts if p.text)
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@@ -131,6 +131,10 @@ async def test_agent_tool_inherits_parent_app_name(monkeypatch):
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)
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return _empty_async_generator()
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async def close(self):
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"""Mock close method."""
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pass
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monkeypatch.setattr('google.adk.runners.Runner', StubRunner)
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tool_agent = Agent(
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Reference in New Issue
Block a user