Cloud BOT MCP for AI. Run complex web tasks through conversation.
Works with every AI agent you already use
…and any MCP-compatible client








How this MCP server connects to your AI agent
Cloud BOT MCP connects your AI agent directly to cloud-based Robotic Process Automation (RPA) platforms. It lets you run automated browser tasks without writing code or logging into dozens of dashboards.
Your AI client acts as a dedicated workflow coordinator, allowing it to scrape data from complex websites, fill out web forms, and manage entire multi-step operations simply by talking to it.
What AI agents can do with Cloud BOT Automation
Cancel job
Stops an automation task that is currently running.
Execute bot
Starts a new bot run, allowing you to pass custom data parameters like URLs or JSON objects.
Get bot details
Retrieves specific configuration and information about an individual automation robot.
List details for every available browser bot setup in your account.
Start a full automation job on any specific bot using custom data inputs.
See if an automated task finished successfully, or retrieve the detailed logs explaining why it failed.
Stop a job immediately if you need to pause the process or check its progress before completion.
List and access files that your bots created or used within the cloud storage system.
Ask an AI about this
Waiting for input…
What AI agents can do with Cloud BOT: 7 Bot Control Functions
These seven tools allow you to programmatically control every aspect of your cloud-based web automation platform through natural language prompts.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Cloud BOT on VinkiusCancel Job
Stops an automation task that is currently running.
Execute Bot
Starts a new bot run, allowing you to pass custom data parameters like URLs or JSON...
Get Bot Details
Retrieves specific configuration and information about an individual automation...
Get Job Status
Checks the current status of a specific job run, whether it's running, succeeded, or...
List Bots
Retrieves a list and metadata for all available browser automation bots in your...
List Cloudbot Files
Lists the files stored in Cloud BOT storage used or generated by your robots.
List Jobs
Shows a list of your most recent completed automation job runs.
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Cloud BOT, then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,100+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
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.
VINKIUS INFRASTRUCTURE
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on every call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
Built on the Model Context Protocol (MCP) for Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This connection provides 7 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
The pain of checking web data manually is clicking through endless dashboards., Solved with Vinkius AI Gateway
Today, getting a full picture of your website performance means logging into the scraping portal, running Bot A for pricing, then switching tabs to run Bot B for form submissions. If anything fails, you have to click around between multiple views—the job list, the log viewer, and the file storage—just to figure out what went wrong.
With this MCP, you don't touch a dashboard. You just talk to your agent: 'Run all three bots and tell me if any failed.' Your AI handles the entire sequence of checks and execution steps behind the scenes. It gets you the answer in plain text—no more clicking required.
Cloud BOT MCP Gives You Full Control Over Automation Jobs
You no longer have to manually monitor each run. Your agent coordinates everything; it triggers the process using `execute_bot`, checks the outcome with `get_job_status`, and gathers the files you need via `list_cloudbot_files`—all within a single, natural chat sequence.
Your AI client acts as your dedicated RPA engineer, giving you comprehensive control over web workflows without ever needing to know how an API call works. You just tell it what needs doing.
What your AI can actually do with this
Forget manually navigating web portals just to check on job progress or extract data. This MCP gives your agent full control over cloud-based browser automation. You can instruct your AI client to perform highly structured tasks—like running a specific scraping bot, coordinating multiple steps, or managing the output files generated by those bots.
It acts like having an operations engineer who lives inside your chat window. Need to check if a job ran successfully? Ask it. Want to trigger a data extraction run using custom parameters? Just ask. You can even manage all the robots themselves and access all stored results within the Vinkius catalog ecosystem, keeping complex web workflows running entirely in conversation.
019dd0d1-6e1a-73e0-aeef-b63421a4bafd Here's how it actually works
The bottom line is that you treat complex web automation like a conversation; you talk to your AI client, and it executes the necessary technical commands behind the scenes.
First, subscribe to this MCP and retrieve your Access Token, Secret Key, and Public ID from the Cloud BOT dashboard.
Next, connect those credentials to your AI client (Claude, Cursor, etc.) through Vinkius. Your agent now has full access to the bot controls.
Finally, tell your agent exactly what you want done—for example, 'Run the price scraper on this URL' or 'List all available bots.' The job runs automatically.
Who is this actually for?
This MCP is built for people whose job requires them to extract data or interact with websites repeatedly. If you're spending time logging into separate portals just to check status or copy-paste results, this tool saves your sanity and your afternoon.
They use the MCP to programmatically list all bots and manage job executions, triggering complex data workflows without leaving their terminal.
They automate lead generation by running scraping bots on target sites and monitoring execution history using natural language commands.
They use the MCP to manage files and check job status after a complex web scrape, ensuring all extracted data points are correctly captured before analysis.
What Changes When You Connect
Automate data extraction instantly. Instead of building custom scripts for every website, you use the execute_bot function to run pre-built bots and get structured data without writing a line of code.
Stay informed about your processes with real-time visibility. Use get_job_status or list_jobs to check if an automated task is running correctly or failed, all via natural language chat.
Keep your project organized by managing outputs. The list_cloudbot_files tool lets you see exactly what data was saved and where it is stored, making file retrieval simple.
Control complex workflows with confidence. If a process goes wrong mid-run, simply ask the agent to cancel_job, preventing wasted time or resources on failed runs.
Manage your entire bot inventory easily. Use list_bots to get an overview of all available automation tools, ensuring you know which bots are ready for deployment.
See it in action
Monitoring competitor pricing changes
A marketing analyst needs daily price data from three different vendor sites. Instead of manually logging into the scraping platform and running each job, they ask their agent to execute_bot for all three bots sequentially. They then use list_jobs to confirm successful runs across the board.
Auditing web form submissions
An ops team needs to verify that a high-value data entry job completed correctly. They instruct their agent to first check the job status using get_job_status and then use list_cloudbot_files to retrieve the final CSV output for review.
Debugging a failing workflow
A developer runs a bot, but it fails. Instead of reading cryptic error codes, they ask their agent to check the logs and use get_bot_details to confirm the correct input parameters were used.
Bulk data harvesting for research
A researcher needs to scrape information from a list of 50 URLs. They first run a query using list_bots to confirm the scraper is ready, then instruct their agent to queue up multiple runs via execute_bot, coordinating the entire batch process in one chat thread.
The honest tradeoffs
Copying/pasting API parameters
Writing out complex JSON payloads for every single job run makes the prompt massive, hard to read, and prone to syntax errors.
Instead of providing raw JSON, let your agent handle it. You simply ask: 'Run the lead capture bot using this list of URLs,' which allows the agent to use execute_bot correctly in the background.
Ignoring job failures
A user assumes a job ran just because they clicked 'run.' They don't know if it timed out or failed due to bad data, so they waste time analyzing incomplete results.
Always confirm the outcome. After triggering any bot run with execute_bot, follow up by asking for its status using get_job_status and checking the logs.
Forgetting cleanup steps
Running many jobs over time fills up the cloud storage, making it hard to find critical data points from weeks ago.
Periodically use list_cloudbot_files or ask your agent to manage the file lifecycle so you always know where the most current and important results are stored.
When It Fits, When It Doesn't
Use this MCP if your process involves interacting with a web browser: clicking, filling forms, scraping tables, or navigating multi-page sites. Think 'browser interaction.' Don't use it if you only need to read data from a database (use a direct SQL connector) or send simple emails (use a messaging tool). If the task requires simulating a human user on a webpage—that’s where this MCP lives. It gives your agent the hands and eyes needed for web automation, letting you manage execution, check status (get_job_status), and handle file results all from one conversation.
Questions you might have
How do I check if a Cloud BOT job ran successfully? +
You use the get_job_status tool to instantly query the outcome of any specific automation job. It tells you immediately if it succeeded, failed, or is still running.
Can I run multiple bots from Cloud BOT using this MCP? +
Yes, you can coordinate multi-bot workflows by calling execute_bot for each bot and then listing all the job IDs with list_jobs. This keeps everything in one conversation thread.
What if I need to stop a running automation task? +
If something goes wrong or you just want to pause it, use the cancel_job function. It sends an immediate signal to halt the process safely and cleanly.
Where do the scraped files go with Cloud BOT MCP? +
The output files are managed in your cloud storage. You can see what's there or manage them using list_cloudbot_files to get a clear inventory of all generated data.
Does Cloud BOT MCP require coding knowledge? +
No, you don't write code. Your AI agent handles the API calls and complex logic for you; you just need to know what web task needs doing.
We've already built the connector for Cloud BOT. Just plug in your AI agents and start using Vinkius.
No hosting. No infrastructure. No complex setup.
All 7 tools are live and waiting.
You're up and running in seconds.
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Built, hosted, and secured by Vinkius. You just connect and go.