What is the difference between Swiss-Prot and TrEMBL entries?

Swiss-Prot contains 570K+ entries that have been manually reviewed and curated by expert biologists — the gold standard for protein annotation. TrEMBL contains 250M+ entries that are computationally annotated from gene sequences. Swiss-Prot entries are marked as 'reviewed' and are highly reliable; TrEMBL entries are automatically generated and may contain errors.

Do I need to register or pay for an API key?

No. UniProt REST API is completely free and open without any authentication. There are no rate limits for reasonable usage patterns. UniProt is funded by the National Institutes of Health (NIH), European Molecular Biology Laboratory (EMBL), and the Swiss Institute of Bioinformatics (SIB).

Can I retrieve full amino acid sequences for proteins?

Yes. Every protein entry includes the full amino acid sequence with length information. The sequence is returned in standard one-letter amino acid code. For very large proteins (10,000+ residues), the sequence may be truncated in the response but the full accession data is always provided for direct download.

UniProt MCP Server for OpenAI Agents SDK 3 tools — connect in under 2 minutes

Name: UniProt
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 3 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect UniProt through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="UniProt Assistant",
            instructions=(
                "You help users interact with UniProt. "
                "You have access to 3 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from UniProt"
        )
        print(result.final_output)

asyncio.run(main())

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About UniProt MCP Server

Connect your AI agent to UniProt — the Universal Protein Resource — the world's definitive knowledge base for protein sequence and functional information.

The OpenAI Agents SDK auto-discovers all 3 tools from UniProt through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries UniProt, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.

What you can do

Protein Search — Find proteins by name, gene symbol, function, or organism across 250M+ entries from both TrEMBL (auto-annotated) and Swiss-Prot (manually curated)
Accession Lookup — Get complete protein data by UniProt accession number (e.g., P04637 for human p53) including function, subcellular location, and full amino acid sequence
Gene Search — Find all proteins encoded by a specific gene name across multiple organisms to compare orthologs and paralogs

The UniProt MCP Server exposes 3 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect UniProt to OpenAI Agents SDK via MCP

Follow these steps to integrate the UniProt MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 3 tools from UniProt

Why Use OpenAI Agents SDK with the UniProt MCP Server

OpenAI Agents SDK provides unique advantages when paired with UniProt through the Model Context Protocol.

Native MCP integration via `MCPServerSse` — pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

UniProt + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the UniProt MCP Server delivers measurable value.

Automated workflows: build agents that query UniProt, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents — one queries UniProt, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through UniProt tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query UniProt to resolve tickets, look up records, and update statuses without human intervention

UniProt MCP Tools for OpenAI Agents SDK (3)

These 3 tools become available when you connect UniProt to OpenAI Agents SDK via MCP:

get_uniprot_protein

Get full protein details by UniProt accession ID

search_uniprot

Returns protein name, gene, organism, function, subcellular location, and sequence. Try: insulin, hemoglobin, p53, BRCA1, spike protein. Search UniProt for proteins by name, function, or keyword

search_uniprot_gene

Returns all protein isoforms and their functional annotations. Find proteins encoded by a specific gene

Example Prompts for UniProt in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with UniProt immediately.

"Tell me about the p53 tumor suppressor protein and its function."

"Find all proteins encoded by the BRCA1 gene."

"Look up UniProt accession Q9BYF1 and show me its full details."

Troubleshooting UniProt MCP Server with OpenAI Agents SDK

Common issues when connecting UniProt to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

UniProt + OpenAI Agents SDK FAQ

Common questions about integrating UniProt MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.