How to Use the UniProt MCP in OpenAI Agents SDK

Q: How do I use UniProt with OpenAI Agents SDK to find protein details?

To find full protein details, you invoke the getuniprotprotein tool and pass the specific UniProt accession ID. The agent then returns all available information tied to that unique identifier.

Q: Can OpenAI Agents SDK search for proteins by function using UniProt?

Yes, you can use searchuniprot. This tool lets your agent query the massive dataset by passing functional keywords. It returns not just names, but also subcellular location and sequence data.

Q: Does UniProt support finding gene isoforms with OpenAI Agents SDK?

Absolutely. The searchuniprotgene tool allows you to input a specific gene name. It returns every protein isoform associated with that gene, along with their functional annotations.

Q: Does the MCP Server support searching for different protein types with OpenAI Agents SDK?

The searchuniprot tool supports querying by name, function, or keyword. You just need to pass those criteria into the search query when building your agent's logic.

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Connect UniProt MCP to OpenAI Agents SDK

Create your Vinkius account to connect UniProt to OpenAI Agents SDK 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 OpenAI Agents SDK

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Discovering Protein Information via MCP Server

You can call `get_uniprot_protein` to pull full details using a specific UniProt accession ID. This function provides an immediate, deep dive into the protein's entire record. Need more than one access code? You’ll use `search_uniprot` to query proteins based on names, functions, or general keywords. It returns key data like the gene name, organism, and sequence.

Tracking Protein Genes with OpenAI Agents SDK

When you need a full picture of related isoforms, run `search_uniprot_gene`. This tool finds all protein isoforms linked to a single specified gene. It also provides their functional annotations. This lets your agent track complex relationships between genes and the proteins they encode, which is critical for research workflows.

Searching UniProt by Keyword

The `search_uniprot` tool handles broad searches. Simply pass a name or function—like 'insulin' or 'p53'—and the agent pulls back the core data: sequence, subcellular location, and organism. It’s fast. You get critical biological context right away without needing multiple specialized lookups.

Setup guide

Set up UniProt MCP in OpenAI Agents SDK

Prerequisites

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

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all UniProt tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives UniProt tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate UniProt tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="UniProt Agent",
            instructions="You have access to UniProt tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about UniProt MCP in OpenAI Agents SDK

To find full protein details, you invoke the `get_uniprot_protein` tool and pass the specific UniProt accession ID. The agent then returns all available information tied to that unique identifier.

Yes, you can use `search_uniprot`. This tool lets your agent query the massive dataset by passing functional keywords. It returns not just names, but also subcellular location and sequence data.

Absolutely. The `search_uniprot_gene` tool allows you to input a specific gene name. It returns every protein isoform associated with that gene, along with their functional annotations.

This MCP Server touches highly technical biological data, specifically massive collections of protein sequences and functional amino acid data. This is standard research data.

The `search_uniprot` tool supports querying by name, function, or keyword. You just need to pass those criteria into the search query when building your agent's logic.

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