How to Use the Kannapedia Cannabis Genetics MCP in Google ADK

Connect Google ADK enterprise agents to the Kannapedia Cannabis Genetics database for deep botanical reasoning.

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Connect Kannapedia Cannabis Genetics MCP to Google ADK

Create your Vinkius account to connect Kannapedia Cannabis Genetics to Google ADK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Kannapedia Cannabis Genetics with Google ADK

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Inject Kannapedia data into Google ADK pipelines

Use the `get_strain_detail` tool to feed verified strain genetics straight into your Gemini agent. Simply define the Google ADK toolset with your Vinkius HTTP parameters to pass it to your agent. This Google integration exposes the genetic database directly to your Gemini model. It allows Gemini to process complex botanical queries using its massive context window.

Analyze terpene profiles alongside BigQuery data

Fetch chemical details using the `search_by_terpene` tool to combine your BigQuery dispensary inventory with the Kannapedia database. Your Google ADK agent can fetch chemical details and run comparisons against your warehouse. The Gemini agent processes both datasets inside its long-context window. It makes it easy to verify if the physical inventory matches the documented genetic profiles.

Filter active tools to restrict agent actions

Limit your Google ADK agent to only use the `search_by_effect` and `search_genetics` tools by filtering the exposed MCP toolset. Control exactly what your Gemini models can access during a live session. This restriction keeps your Google Cloud enterprise agents focused on safe, informational strain lookups. It prevents Gemini from trying to call unauthorized genetic database operations during a conversation.

Setup guide

Set up Kannapedia Cannabis Genetics MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Kannapedia Cannabis Genetics tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Kannapedia Cannabis Genetics_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Kannapedia Cannabis Genetics tools via MCP.",
    tools=mcp_tools,
)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Kannapedia. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Kannapedia Cannabis Genetics MCP in Google ADK

Instantiate the toolset using the streamable HTTP parameters pointing to your Vinkius MCP endpoint. Pass that toolset to your agent constructor to let Gemini call `get_strain_detail`.

Yes. Use the tool name filter when defining your toolset in the SDK. This lets you expose only `search_by_effect` while hiding the lineage tools.

Gemini can ingest dozens of detailed genetic profiles returned by `search_genetics`. The model analyzes these long text payloads to find patterns that simple search engines miss.

Yes. The Vinkius infrastructure supports both connection types. You can run the server locally via Stdio for development or use the hosted HTTP endpoint for production.

Yes. Your queries for specific strains and terpenes are executed inside ephemeral V8 isolates. No search history is stored on the host, ensuring your market research remains confidential.

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