How to Use the UniProt MCP in Google ADK

Q: How can I use UniProt with Google ADK to get protein details?

You invoke getuniprotprotein and supply the specific UniProt accession ID. Your agent then retrieves a complete record, which is ideal for passing into Vertex AI models.

Q: Does Google ADK allow searching UniProt by function?

Yes, use searchuniprot. You pass the functional keyword or name, and it returns details like subcellular location and sequence. This is a core feature for general biological querying.

Q: Can I find gene isoforms using UniProt with Google ADK?

The searchuniprotgene tool handles this. You feed it the gene name, and it returns all associated protein isoforms plus their annotations. This helps build a complete picture of genetic activity.

Q: How do I search for proteins using UniProt with Google ADK?

Use the searchuniprot tool. It accepts keywords, names, or functions and returns key metadata like organism, gene, and sequence in a single operation.

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Connect UniProt MCP to Google ADK

Create your Vinkius account to connect UniProt 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 UniProt with Google ADK

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Getting Full Protein Details in Google ADK

The `get_uniprot_protein` tool provides full protein details when you give it a UniProt accession ID. This function immediately gives your agent deep insight into the protein's entire profile. It’s perfect for enterprise analysis because you get all structured data in one call, feeding directly into BigQuery.

Searching UniProt with Google ADK

Use `search_uniprot` to find proteins when you know the name, function, or just a general keyword. The tool returns names, genes, organism data, subcellular location, and sequences. This mechanism lets your agent perform broad searches without needing dozens of specific database calls.

Tracking Gene Isoforms via MCP Server

When you need all the related proteins for one gene, call `search_uniprot_gene`. This tool pulls back every single protein isoform and their functional annotations. It’s a massive help for large-scale biological data modeling, letting your agent map out complex genetic relationships.

Setup guide

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by UniProt. 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 UniProt MCP in Google ADK

You invoke `get_uniprot_protein` and supply the specific UniProt accession ID. Your agent then retrieves a complete record, which is ideal for passing into Vertex AI models.

Yes, use `search_uniprot`. You pass the functional keyword or name, and it returns details like subcellular location and sequence. This is a core feature for general biological querying.

The `search_uniprot_gene` tool handles this. You feed it the gene name, and it returns all associated protein isoforms plus their annotations. This helps build a complete picture of genetic activity.

The server manages massive amounts of biological data, specifically amino acid sequences and functional annotation details from over 250 million protein records. This is highly specialized research data.

Use the `search_uniprot` tool. It accepts keywords, names, or functions and returns key metadata like organism, gene, and sequence in a single operation.

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