How to Use the WorldNewsAPI MCP in CrewAI

Q: How do I use WorldNewsAPI with CrewAI to manage complex research topics?

You start by using the searchworldnews tool. This lets your autonomous crew focus immediately on a keyword, skipping the noise. The resulting articles can then be handed off for deeper analysis.

Q: What happens if I need to confirm the WorldNewsAPI connection before running CrewAI tasks?

You call checkapistatus. This tells you right away whether the whole service is operational. It's a quick, non-destructive check that ensures your multi-agent workflow won't fail unexpectedly.

Q: Does WorldNewsAPI with CrewAI handle specific language requirements?

Absolutely. When you use gettopworldnews, you define the target language and country upfront. This keeps your initial data set highly filtered, so your agents only process what's relevant.

Q: Can WorldNewsAPI with CrewAI process data from a specific source URL?

Yes, that’s what extractnewsfromurl does. Just give the tool a link, and it extracts everything you need—the core article text and supporting metadata—into a usable format for your crew.

Get structured world news data and run complex operations with CrewAI.

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Create your Vinkius account to connect WorldNewsAPI 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 WorldNewsAPI with CrewAI

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Searching World News with MCP Server

CrewAI agents can search for articles using `search_world_news`. You just pass in a keyword or phrase, and the API returns relevant headlines instantly. This lets your research agent quickly narrow down topics instead of sifting through general feeds. It's perfect when you need to focus an investigation on specific subjects.

Deep Content Retrieval for CrewAI Agents

Need the full text from a news article? Use `extract_news_from_url`. Your agent passes in a URL, and it pulls out all the main content along with associated metadata. This means your analysis agent gets more than just a headline; it gets the raw material it needs to write detailed reports. The data comes structured, making it usable immediately.

Getting Global Headlines in CrewAI

To start a mission, your agent can use `get_top_world_news`. You specify the country and language you want, and the API gives you the current top headlines for that region. This is great for setting the initial scope of a crew's work. If you need to run an analysis focused on Japan or Brazil, this tool sets up that starting point.

Setup guide

Set up WorldNewsAPI 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 WorldNewsAPI tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent WorldNewsAPI 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="WorldNewsAPI Analyst",
        goal="Access and analyze WorldNewsAPI data via MCP.",
        backstory="Expert analyst with direct WorldNewsAPI access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent WorldNewsAPI 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 WorldNewsAPI. 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 WorldNewsAPI MCP in CrewAI

You start by using the `search_world_news` tool. This lets your autonomous crew focus immediately on a keyword, skipping the noise. The resulting articles can then be handed off for deeper analysis.

You call `check_api_status`. This tells you right away whether the whole service is operational. It's a quick, non-destructive check that ensures your multi-agent workflow won't fail unexpectedly.

Absolutely. When you use `get_top_world_news`, you define the target language and country upfront. This keeps your initial data set highly filtered, so your agents only process what's relevant.

This server touches public article content, metadata (like publication dates), and keywords. It doesn't handle any private user accounts or personally identifiable information; it only pulls published news material.

Yes, that’s what `extract_news_from_url` does. Just give the tool a link, and it extracts everything you need—the core article text and supporting metadata—into a usable format for your crew.

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