How to Use the GenBank/NCBI API MCP in CrewAI

Q: How can one CrewAI agent find sequences from the GenBank/NCBI API and another one analyze them?

Assign the searchncbisequences tool to a 'Researcher' agent. It finds the UIDs and places them in the context. A second 'Analyst' agent then accesses those UIDs and uses getncbisummary to get the details.

Deploy a crew of bioinformatic agents. Let them research, analyze, and monitor NCBI sequence data for you with CrewAI.

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Connect GenBank/NCBI API MCP to CrewAI

Create your Vinkius account to connect GenBank/NCBI API to CrewAI 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 GenBank/NCBI API with CrewAI

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Delegate Sequence Discovery

Assign a 'Researcher' agent the task of finding relevant sequences using `search_ncbi_sequences`. This agent can take a high-level goal, like 'find all human KRAS protein variants,' and execute the specific queries needed. A 'Data Curator' agent can then take the list of UIDs from the Researcher. Its job is to use `get_ncbi_summary` on each UID to fetch the details. The two agents work together, passing the data through CrewAI's shared memory.

Autonomous Pipeline Monitoring

Set up a 'Monitor' agent whose only job is to run `check_api_status` every few minutes. If the NCBI API goes down, it passes that context to an 'Operator' agent. The Operator can then pause other agents that rely on the GenBank/NCBI API. You could also have a 'Scout' agent that periodically runs `list_ncbi_databases`. If a new database appears, it can trigger a 'Discovery' agent to start exploring it with `search_ncbi_sequences`, creating a self-updating research pipeline.

Build a CrewAI Research MCP Server

Adding this MCP Server to your crew is easy. Just pass the Vinkius URL into your Agent's `mcps` list. CrewAI handles the connection, and your agents can immediately start using tools like `search_ncbi_sequences` to do their work. This setup lets you build specialized roles. One agent can be an expert on the 'protein' database, another on 'nuccore'. They don't need to know the implementation details of the NCBI API, just how to use the tools provided by the MCP to accomplish their assigned tasks.

Setup guide

Set up GenBank/NCBI API MCP in CrewAI

Prerequisites

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

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke GenBank/NCBI API tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="GenBank/NCBI API Analyst",
    goal="Access and analyze GenBank/NCBI API data via MCP.",
    backstory="Expert analyst with direct GenBank/NCBI API access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent GenBank/NCBI API transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="GenBank/NCBI API Analyst",
        goal="Access and analyze GenBank/NCBI API data via MCP.",
        backstory="Expert analyst with direct GenBank/NCBI API access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent GenBank/NCBI API transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

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 GenBank/NCBI. 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 GenBank/NCBI API MCP in CrewAI

Assign the `search_ncbi_sequences` tool to a 'Researcher' agent. It finds the UIDs and places them in the context. A second 'Analyst' agent then accesses those UIDs and uses `get_ncbi_summary` to get the details.

Yes, create a dedicated agent with a simple task: 'Check the NCBI API status every 5 minutes using `check_api_status` and report if it is not operational'. This is a perfect job for a specialized monitoring agent in a crew.

A 'Strategist' agent could define a query. A 'Researcher' uses `search_ncbi_sequences` to get UIDs. An 'Enricher' uses `get_ncbi_summary` on the UIDs. Finally, a 'Synthesizer' agent writes a report based on the collected summaries.

When you configure the MCP server in CrewAI, you can use the `tool_filter` argument. This lets you expose only `search_ncbi_sequences` to one agent and `get_ncbi_summary` to another, enforcing role specialization.

No. The queries your agents make for sequence information are stateless. They are processed in an isolated, ephemeral Vinkius environment and proxied to NCBI. No part of the genomic query payload is ever stored.

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