How to Use the Ensembl MCP in Google ADK

Q: How is the Ensembl MCP server configured in Google ADK?

Initialize an McpToolset with the server URL and pass it to your LlmAgent. Google ADK handles the connection, exposing the tools to your agent's reasoning loop.

Q: Does Google ADK support filtering Ensembl tools?

Yes. You can use the toolnames filter in your McpToolset configuration to expose only the specific functions your agent needs, keeping your workspace uncluttered.

Q: Can I use Ensembl with Google ADK for variant analysis?

Absolutely. Your agent can call getvariation or searchga4ghvariants to pull population data directly into your analysis workflow.

Query Ensembl genomic databases directly from Google ADK agents and scale your biological research.

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Connect Ensembl MCP to Google ADK

Create your Vinkius account to connect Ensembl 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 Ensembl with Google ADK

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Native genomic data access for Google ADK

Your agents can now fetch sequences using `get_sequence_id` or `get_sequence_region` without leaving the Google Cloud environment. This integration allows your agent to pull raw data into your existing BigQuery-linked pipelines, bypassing the need for custom middleware.

Complex gene tree navigation

Use `get_genetree` to resolve evolutionary relationships directly within your Google ADK agent logic. It provides the raw tree data your agent needs to compare homology across species, giving you high-fidelity insights without the boilerplate code.

Taxonomic and ontological search

Your agent can find exact terms using `get_taxonomy_id` or `get_ontology_id` to standardize your research data. This toolset ensures your agent speaks the same language as your genomic databases, reducing ambiguity in your automated analysis tasks.

Setup guide

Set up Ensembl 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 Ensembl 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="Ensembl_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Ensembl tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Ensembl MCP in Google ADK

Initialize an `McpToolset` with the server URL and pass it to your `LlmAgent`. Google ADK handles the connection, exposing the tools to your agent's reasoning loop.

Yes. You can use the tool_names filter in your `McpToolset` configuration to expose only the specific functions your agent needs, keeping your workspace uncluttered.

Absolutely. Your agent can call `get_variation` or `search_ga4gh_variants` to pull population data directly into your analysis workflow.

It operates as a streamable HTTP connection. The agent establishes the link when needed and closes it when the task is finished, keeping your environment ephemeral.

The server manages your requests as isolated, ephemeral calls. Your genomic search parameters are never cached or stored, ensuring your specific research queries remain private to your agent session.

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