How to Use the NewsAPI MCP in CrewAI

Q: How do I connect the NewsAPI MCP Server to my CrewAI setup?

Install crewaitools. You can pass the Vinkius URL directly into your agent's mcps array, or use MCPServerHTTP for advanced configuration.

Q: Can I restrict which NewsAPI tools a CrewAI agent can use?

Yes. Use the toolfilter parameter when setting up the MCP server in CrewAI. You can give your researcher agent access to searchheadlines while hiding listsources.

Deploy autonomous research teams in CrewAI powered by real-time global news data via NewsAPI.

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Connect NewsAPI MCP to CrewAI

Create your Vinkius account to connect NewsAPI 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 NewsAPI with CrewAI

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Assign News Gathering to CrewAI Agents

The NewsAPI MCP Server acts as a dedicated research endpoint for your CrewAI agents. Don't make one agent do all the work. You can assign this server to a specific researcher agent. Its sole job is to monitor global events using `get_headlines_by_country` and `get_recent_articles`. Once the researcher pulls the raw data, it passes the context to an analyst agent. The analyst processes the text and decides if the crew needs to trigger a deeper `search_articles` query to find historical precedents.

Build Specialized Media Monitors

The `get_articles_from_domains` tool turns a CrewAI agent into a strict financial news monitor. You can restrict its scope to specific business publications. The agent ignores the broader internet and focuses only on high-signal sources. The agent runs autonomously, checking for updates. When a major story breaks, it alerts a moderator agent. You get a fully automated newsroom operating without human intervention.

Map the Global Narrative

The `get_articles_by_language` tool pulls reports from different regions simultaneously to map global narratives. Tracking a story across borders requires multiple perspectives. Your crew can divide and conquer the international press. One agent grabs the Spanish reports, another pulls the English versions, and a third cross-references them using `get_popular_articles`. They share memory and build a complete picture of the global response.

Setup guide

Set up NewsAPI 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 NewsAPI tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Install `crewai[tools]`. You can pass the Vinkius URL directly into your agent's `mcps` array, or use `MCPServerHTTP` for advanced configuration.

Yes. Use the `tool_filter` parameter when setting up the MCP server in CrewAI. You can give your researcher agent access to `search_headlines` while hiding `list_sources`.

CrewAI agents share memory. When your researcher agent calls `get_headlines_by_category`, the returned JSON is stored in the crew's shared context for the analyst agent to read and process.

Yes. You can set up your crew to run sequentially or hierarchically on a schedule. The agents wake up, hit the news endpoints, and escalate any critical findings based on your rules.

The server processes your specific search keywords and domain filters. Vinkius routes these requests through ephemeral, zero-trust infrastructure. The execution container evaporates the moment the API responds, ensuring your proprietary research topics remain completely private.

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