How to Use the X (Twitter) MCP in CrewAI

Q: Can I use CrewAI for autonomous user lookups on X (Twitter)?

Yes. You can assign an agent to execute lookupuserbyusername, getting full profile details, which the crew then uses as a definitive source of truth for subsequent tasks.

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Connect X (Twitter) MCP to CrewAI

Create your Vinkius account to connect X (Twitter) 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 X (Twitter) with CrewAI

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Analyze Tweet Data Across Agents

Give the `get_tweet_details` tool to a specialist agent. This agent pulls the text and engagement metrics of an X (Twitter) tweet by ID, then passes those raw numbers to another agent for analysis. The collaboration structure means one agent can research the data while a second agent independently calculates sentiment based on the returned metrics.

Profile Gathering with Specialized Agents

Assign user profile retrieval using `lookup_user_by_username` to an 'Intelligence Agent'. This agent gets all the core details (bio, follower count) and then shares that structured memory with a 'Reporting Agent' for summary generation. The shared memory ensures that every piece of information gathered—like verification status—is available across multiple steps in the autonomous workflow.

Automated X (Twitter) Search Operations

A dedicated 'Monitoring Agent' uses `search_recent_tweets` to gather public X (Twitter) posts using specific hashtags. This agent then passes the raw search results to a 'Triage Agent' for immediate keyword filtering. This process mimics real-world team operation: one agent monitors, and another acts on the filtered data.

Setup guide

Set up X (Twitter) 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 X (Twitter) tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent X (Twitter) 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 X (Twitter). 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 X (Twitter) MCP in CrewAI

You assign specialized roles to your agents. For example, Agent A researches recent tweets with `search_recent_tweets`, and Agent B analyzes the results for sentiment.

The system provides the raw text, along with quantitative engagement metrics. This combination allows your agents to perform detailed analysis and reporting on social trends.

Yes. You can assign an agent to execute `lookup_user_by_username`, getting full profile details, which the crew then uses as a definitive source of truth for subsequent tasks.

The server handles public social intelligence: tweet text, engagement metrics, user profiles, and search result sets. All data is read-only for your autonomous operations.

The server works with public domain information: user profile names, tweet text, and engagement metrics. The crew handles processing this publicly available social data.

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