How to Use the NCDC Climate Data Online MCP in CrewAI

Q: How do I add the NCDC Climate Data Online MCP server to my CrewAI setup?

Pass your Vinkius endpoint directly into the mcps array on your Agent definition. CrewAI handles the HTTP connection automatically.

Q: Can I restrict which NCDC Climate Data Online MCP Server tools an agent uses?

Yes. Use MCPServerHTTP from crewai.mcp and apply a toolfilter. You can give the scout agent access to location tools while restricting the analyst to data retrieval tools.

Deploy autonomous agent crews to analyze historical weather patterns with CrewAI and this MCP server.

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Connect NCDC Climate Data Online MCP to CrewAI

Create your Vinkius account to connect NCDC Climate Data Online 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 NCDC Climate Data Online with CrewAI

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Assign agents to map weather stations

The `list_stations` tool gives your research agent a complete list of observation points. Your agent uses `get_station` to verify the operational dates and elevation of each site. CrewAI allows you to dedicate a specific agent entirely to location scouting. Once it finds the right station, it passes the exact ID to an analysis agent for the next phase.

Extract data with the NCDC Climate Data Online MCP Server

The `get_climate_data` tool pulls the actual historical records for the target station. Your analysis agent runs this tool after receiving the station ID from the scout. Look—it reviews the raw payload, extracts the temperature metrics, and hands the clean data over to a reporting agent. The crew handles the entire pipeline autonomously.

Determine exact meteorological metrics

The `list_data_categories` tool reveals what broad data types exist for a location. After that, `list_data_types` narrows the focus down to specific variables like daily maximum temperature. Your crew dynamically adjusts its extraction strategy based on what these tools return. If a specific metric is missing, the agent pivots to an alternative data type without human intervention.

Setup guide

Set up NCDC Climate Data Online 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 NCDC Climate Data Online tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent NCDC Climate Data Online 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 →

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="NCDC Climate Data Online Analyst",
        goal="Access and analyze NCDC Climate Data Online data via MCP.",
        backstory="Expert analyst with direct NCDC Climate Data Online access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent NCDC Climate Data Online 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 NCDC Climate Data Online. 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 NCDC Climate Data Online MCP in CrewAI

Pass your Vinkius endpoint directly into the `mcps` array on your Agent definition. CrewAI handles the HTTP connection automatically.

Yes. Use `MCPServerHTTP` from `crewai.mcp` and apply a `tool_filter`. You can give the scout agent access to location tools while restricting the analyst to data retrieval tools.

Agents operate with shared memory. When one agent pulls a station ID from the MCP server, the next agent in the sequence reads that ID from context and uses it.

It defaults to Streamable HTTP for remote servers. The framework connects, executes the tool, and parses the response cleanly.

The system only processes search strings like dataset names and date ranges. Zero-trust architecture ensures your specific research parameters are never logged or stored by the host infrastructure.

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