How to Use the Winston AI MCP in CrewAI

Build autonomous operations by having specialized agents collaborate using CrewAI.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Winston AI MCP to CrewAI

Create your Vinkius account to connect Winston AI 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.

GDPR Free for Subscribers

Setup Winston AI with CrewAI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Autonomous Plagiarism Audits

You can assign a 'Researcher Agent' to use `check_plagiarism_url` and then have an 'Analyst Agent' take the output. This collaboration allows you to check multiple sources automatically, building reports without human input. The shared memory of CrewAI ensures that all agents know the results from previous steps, letting them pass context like text strings between roles.

Multi-stage Content Verification

Set up a crew where one agent researches facts using `fact_checker`. A second agent then verifies those findings against multiple sources using `fact_checker_file`. The workflow executes sequentially, and the moderator agent compiles the final report. This process is powerful for handling complex data types like documents; it moves from initial research to multi-source verification autonomously.

AI Content Screening Teams

You can build a team dedicated solely to screening. Agent A runs `detect_ai_text` on submitted text, and Agent B uses `detect_ai_image` if the submission includes an image URL. The final action agent then takes both outputs. The crew handles these multiple steps in a defined order, making sure all necessary content types (text, images) are screened.

Setup guide

Set up Winston AI 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 Winston AI tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Winston AI 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 Winston AI. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Winston AI now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Winston AI MCP in CrewAI

You pass the MCP server URL to the crew definition. The specialized agents then gain access to tools like `check_plagiarism_text`, allowing them to operate autonomously within their assigned roles.

Yes. You can assign a 'Fact Checker Agent' whose sole job is running `fact_checker_url`. This agent works alongside others to ensure all parts of the operation are verified.

The server handles multiple Content formats, including text strings, document URLs, and image detection via URL. The autonomous agents manage these types, ensuring the process is documented.

The crew runs a sequence: an agent retrieves text from a URL and passes it to `check_plagiarism_url`. Another agent then analyzes that output against established institutional standards.

It does. You can build a monitoring crew where one agent detects AI in text using `detect_ai_text`, and another flags the result for human review, completing an end-to-end operational loop.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript