How do I find my Cloud BOT API credentials?

Log in to your account, navigate to the **API Settings** section, and you will find your Access Token, Secret Key, and Public ID.

Can I pass custom parameters to a bot?

Yes! The `execute_bot` tool accepts a `params_json` string where you can provide a JSON object matching your bot's input configuration.

How do I check the results of an automation?

Use the `get_job_status` tool with a job ID to retrieve the execution status and any outputs or files generated by the bot.

INSTANT PLUG AND PLAY

Cloud BOT MCP Server for CrewAIGive CrewAI instant access to 7 tools to Cancel Job, Execute Bot, Get Bot Details, and more

Name: Cloud BOT
Availability: InStock
Author: Vinkius

Built by Vinkius GDPR 7 Tools Framework

Connect your CrewAI agents to Cloud BOT through Vinkius, pass the Edge URL in the `mcps` parameter and every Cloud BOT tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Use with Your AI Agent

Ask AI about this App Connector for CrewAI

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The Cloud BOT app connector for CrewAI is a standout in the Productivity category — giving your AI agent 7 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Cloud BOT Specialist",
    goal="Help users interact with Cloud BOT effectively",
    backstory=(
        "You are an expert at leveraging Cloud BOT tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Cloud BOT "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 7 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Cloud BOT MCP Server

Connect your Cloud BOT account to any AI agent and take full control of your cloud-based Robotic Process Automation (RPA) and browser-based workflows through natural conversation.

When paired with CrewAI, Cloud BOT becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Cloud BOT tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Robot Orchestration — List and manage all browser automation robots in your account programmatically, retrieving detailed configuration and input parameter metadata
Automated Job Execution — Programmatically trigger bot executions with custom JSON parameters to coordinate high-fidelity web scraping and data entry tasks
Workflow Monitoring — Track the real-time status of your automation jobs and retrieve detailed logs and results to maintain perfectly coordinated RPA operations
File Architecture — Access and manage files within the Cloud BOT storage used or generated by your robots to maintain high-fidelity data cycles
Lifecycle Management — Programmatically cancel or suspend running jobs and verify API connectivity directly through your agent for instant operational reporting

The Cloud BOT MCP Server exposes 7 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 7 Cloud BOT tools available for CrewAI

When CrewAI connects to Cloud BOT through Vinkius, your AI agent gets direct access to every tool listed below — spanning rpa, web-scraping, no-code, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

cancel_job

Cancel a running job

execute_bot

You can pass optional input parameters as a JSON string. Trigger a bot execution

get_bot_details

Get details for a specific bot

get_job_status

Check the status of a job

list_bots

List all available RPA bots

list_cloudbot_files

List files in Cloud BOT storage

list_jobs

List recent execution jobs

Connect Cloud BOT to CrewAI via MCP

Follow these steps to wire Cloud BOT into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 7 tools from Cloud BOT

Why Use CrewAI with the Cloud BOT MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Cloud BOT through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Cloud BOT + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Cloud BOT MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Cloud BOT for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Cloud BOT, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Cloud BOT tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Cloud BOT against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for Cloud BOT in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Cloud BOT immediately.

"List all available browser robots in my Cloud BOT account."

"Execute the 'Price Scraper' bot (ID: 'bot_123') with URL 'vinkius.com'."

"Show the status and logs for automation job 'job_456'."

Troubleshooting Cloud BOT MCP Server with CrewAI

Common issues when connecting Cloud BOT to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Cloud BOT + CrewAI FAQ

Common questions about integrating Cloud BOT MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.