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docs: Google ADK integration (#2034)

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* docs: Google ADK integration

Signed-off-by: Anush008 <anushshetty90@gmail.com>

* Update links to Qdrant MCP Server documentation

---------

Signed-off-by: Anush008 <anushshetty90@gmail.com>
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2025-12-11 12:55:27 +05:30
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qdrant-landing/content/documentation/frameworks/_index.md
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| [Feast](/documentation/frameworks/feast/) | Open-source feature store to operate production ML systems at scale as a set of features. |
| [Fifty-One](/documentation/frameworks/fifty-one/) | Toolkit for building high-quality datasets and computer vision models. |
| [Genkit](/documentation/frameworks/genkit/) | Framework to build, deploy, and monitor production-ready AI-powered apps. |
| [Google ADK](/documentation/frameworks/google-adk/) | Open-source Python framework from Google for building, evaluating, and deploying AI agents. |
| [Haystack](/documentation/frameworks/haystack/) | LLM orchestration framework to build customizable, production-ready LLM applications. |
| [HoneyHive](/documentation/frameworks/honeyhive/) | AI observability and evaluation platform that provides tracing and monitoring tools for GenAI pipelines. |
| [Lakechain](/documentation/frameworks/lakechain/) | Python framework for deploying document processing pipelines on AWS using infrastructure-as-code. |
qdrant-landing/content/documentation/frameworks/google-adk.md
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---
title: Google ADK
---
# Google ADK
[Agent Development Kit (ADK)](https://github.com/google/adk-python) is an open-source, code-first Python framework from Google for building, evaluating, and deploying sophisticated AI agents. While optimized for Gemini, ADK is model-agnostic and compatible with other frameworks.
You can connect ADK agents to Qdrant using the [Qdrant MCP Server](https://github.com/qdrant/mcp-server-qdrant/), giving your agent the ability to store and retrieve information using semantic search.
## Installation
```bash
pip install google-adk
```
## Usage
```python
from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import StdioConnectionParams
from mcp import StdioServerParameters
QDRANT_URL = "http://localhost:6333"
COLLECTION_NAME = "my_collection"
root_agent = Agent(
model="gemini-2.5-pro",
name="qdrant_agent",
instruction="Help users store and retrieve information using semantic search",
tools=[
McpToolset(
connection_params=StdioConnectionParams(
server_params=StdioServerParameters(
command="uvx",
args=["mcp-server-qdrant"],
env={
"QDRANT_URL": QDRANT_URL,
"COLLECTION_NAME": COLLECTION_NAME,
}
),
timeout=30,
),
)
],
)
```
For available tools and configuration options, see the [Qdrant MCP Server documentation](https://github.com/qdrant/mcp-server-qdrant/).
## Further reading
- [Google ADK Documentation](https://google.github.io/adk-docs/)
- [Google ADK GitHub Repository](https://github.com/google/adk-python)