How to Use the Cloud BOT MCP in CrewAI

Q: How do I pass Cloud BOT tools to a CrewAI agent?

Add the Vinkius endpoint URL to the mcps list when initializing your agent. The framework automatically imports tools like executebot and makes them available for task execution.

Q: Can a CrewAI agent monitor an active Cloud BOT job?

Yes, you assign a monitor agent to poll getjobstatus while other agents process already completed tasks. This parallel execution keeps your multi-agent workflows moving efficiently.

Q: Can CrewAI agents access files saved by Cloud BOT?

Yes, a specialized data-retrieval agent uses listcloudbotfiles to find the output files. The agent then reads the files to extract the scraped data for the rest of the crew.

Coordinate multi-agent browser scraping teams using CrewAI and the Cloud BOT MCP Server.

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Connect Cloud BOT MCP to CrewAI

Create your Vinkius account to connect Cloud BOT 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 Cloud BOT with CrewAI

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Run multi-agent browser tasks via CrewAI

This MCP Server provides your multi-agent teams with real-time web automation capabilities. Your CrewAI scraper agent initiates web tasks using `execute_bot` while a separate analyst agent waits for the resulting data. If the scraper agent runs into a captcha or layout change, the supervisor agent calls `cancel_job` to halt execution. The team then collaborates to select a different target from the list of available automations.

Let CrewAI agents select the right browser bot

This MCP Server exposes your entire catalog of automated tasks to your agent team. Your CrewAI coordinator uses `list_bots` to inspect available workflows, then reads specific schemas using `get_bot_details` to map user inputs. This setup lets the team choose the exact bot needed for a specific website dynamically. The agents configure the parameters on the fly without hardcoded routing rules.

Audit automation runs using this MCP Server

This MCP Server gives your supervisor agents full visibility over the team's operational history. Your CrewAI auditor agent calls `list_jobs` to review recent browser runs and ensure none are hanging or failing repeatedly. By analyzing past execution metadata, the auditor agent flags patterns of failure on specific websites. It then adjusts the team's scraping schedule to avoid peak traffic times or known site maintenance windows.

Setup guide

Set up Cloud BOT 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 Cloud BOT tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Add the Vinkius endpoint URL to the `mcps` list when initializing your agent. The framework automatically imports tools like `execute_bot` and makes them available for task execution.

Yes, you assign a monitor agent to poll `get_job_status` while other agents process already completed tasks. This parallel execution keeps your multi-agent workflows moving efficiently.

The executing agent detects the failure, and your supervisor agent can call `list_jobs` to inspect the error log. Based on the logs, the crew can decide to retry or notify a human operator.

Yes, a specialized data-retrieval agent uses `list_cloudbot_files` to find the output files. The agent then reads the files to extract the scraped data for the rest of the crew.

All scraped files, cookies, and session data remain in secure cloud storage. Your CrewAI agents only interact with the files via temporary URLs, keeping your local environment free of raw, unencrypted web data.

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