Browserbear MCP. Run scripts, scrape data, or snap screenshots from any website.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
Browserbear automates browser tasks directly from your AI client. You can scrape data, run automated scripts, or grab high-resolution screenshots from any website without opening a dashboard.
It’s designed for agents that need to interact with web pages like a human user does.
What your AI agents can do
Create task
Builds and saves an entirely new automated script for later execution.
Delete run
Removes a record of a completed task run from your history.
Get account usage
Retrieves current metrics on how much of your automated capacity you've used.
Start, monitor, or stop complex browser scripts using specific URLs or form data.
Take high-quality screenshots of any web page with custom dimensions and wait times.
List, inspect, and organize all the automated tasks you've saved for future use.
Check usage statistics to track how many resources your automation is consuming.
Ask AI about this MCP
Supported MCP Clients
OAuth 2.0 Compatible Gemini Waiting for input…
Browserbear: 10 Automation Tools
Manage every step of your web automation process here. From creating new tasks to capturing visual data, these tools give your agent full control over the browser.
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 Browserbear on Vinkius019d7564create task
Builds and saves an entirely new automated script for later execution.
019d7564delete run
Removes a record of a completed task run from your history.
019d7564get account usage
Retrieves current metrics on how much of your automated capacity you've used.
019d7564get run
Checks the status and results associated with a specific, completed task run record.
019d7564get task
Retrieves all details for one particular automated script you've saved.
019d7564list projects
Shows a list of all separate projects you have set up in the account.
019d7564list runs
Lists every recorded instance of task runs that have happened over time.
019d7564list tasks
Retrieves a list of all the individual automated tasks currently saved to your account.
019d7564run task
Triggers an execution run for a specific, pre-built task script.
019d7564take screenshot
Captures and returns a high-quality image of a specified URL.
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 Browserbear, then connect any of our 4,800+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,800+ 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 Browserbear. 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
Works with 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 server provides 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
The manual headache of web testing and data gathering
Today, getting reliable data from a website means copying URLs into a test dashboard. If you need visual proof that a button works, you take a screenshot, save it to Notion, and link it in a Slack thread. For scraping, you open the site, right-click everything, and manually copy blocks of text into Excel.
It’s slow, tedious work. It requires jumping between five different tools—a browser, a clipboard, a dashboard, a ticketing system, and a spreadsheet. The effort is spent managing the data flow, not analyzing it.
Browserbear allows you to automate web tasks with Browserbear
With this MCP, you skip all those manual steps. Your agent simply runs the necessary task through your chat client. You ask for a screenshot of the 'Payment Confirmation' page; it returns the image directly. You need data? It executes the scraper and gives you structured JSON.
The result is an end-to-end process that moves from web interaction to actionable data in seconds, not hours.
What you can do with this MCP connector
Need to automate anything happening in a web browser? This MCP connects your AI agent directly to the power of Browserbear. You can orchestrate complex workflows, running scripted tasks or simply taking quick snapshots of any URL. Imagine having an agent that doesn't just read text; it clicks buttons, fills out forms, and navigates sites exactly like you would.
It’s built for deep web interaction.
This lets your agent retrieve structured data from a complex form, then use that data in another process—like sending scraped leads to a CRM MCP or validating the output against a database MCP. This ability to chain web scraping with other actions is where the power hits home. Since every call routes through Vinkius, you get full visibility into exactly what was called and how much budget was used for every step of the automated process.
019d7564-77cf-7143-8c8a-20eeb310ba1e 
How Browserbear MCP Works
- 1 Subscribe to the Browserbear MCP and enter your API key.
- 2 Tell your AI agent exactly what needs to happen (e.g., 'Take a screenshot of X' or 'Run task Y for Z data').
- 3 The agent executes the web action through this MCP, returning the resulting data or visual output to you.
The bottom line is: your agent treats the entire internet like an API endpoint it can control.
Who Is Browserbear MCP For?
This connector is for technical roles—QA Engineers, Growth Marketers, and Developers. You're the person tired of clicking through dashboards or manually copying data from a web page into a spreadsheet every single day.
Needs to quickly trigger visual regression tests across multiple staging environments and inspect failure results without touching the manual dashboard.
Automates lead gathering or competitor monitoring by scraping public data from niche websites directly into their workflow tool.
Integrates complex, multi-step browser interactions (like submitting a form after logging in) into code using natural language prompts.
What Changes When You Connect
- You get visual confirmation on every run. Whether you use
take_screenshotor monitor a task viaget_run, you always know exactly what the web page looked like when the process finished. - Stop building scripts from scratch. Use
list_tasksto see all your saved templates, and then trigger them instantly withrun_task, even overriding details like the starting URL on the fly. - Manage complexity without hitting a dashboard. You can use natural language prompts to call tools like
list_projectsorget_account_usage, making it feel like talking to a teammate rather than running API calls. - Build powerful pipelines that cross boundaries. Scrape data with Browserbear, then send the structured results to another service MCP—all in one conversation thread.
- Maintain full oversight of your operations history. You can use
list_runsandget_runto audit every action taken by your agent or team.
Real-World Use Cases
Validating a critical checkout flow
A QA engineer needs to check the payment page on five different devices. Instead of manually logging into a dashboard, they simply ask their agent to run the 'Checkout Flow' task and capture screenshots using take_screenshot for each specific URL variation.
Monitoring competitor pricing
A growth marketer needs daily price data from five rival sites. They set up a scraping script, then ask their agent to execute the 'Daily Scraper' task and retrieve the structured output using get_run for immediate analysis.
Investigating failed user signups
A developer wants to diagnose why a specific form submission failed. They use their agent to run the 'Login Flow' task, passing in the known failing credentials, and then inspect the results using get_task.
Auditing old automation runs
An operations manager needs to see all tasks executed last month. They ask their agent to list all history records using list_runs, giving them a complete, auditable log without manual querying.
The Tradeoffs
Trying to run a task before listing it
The user tells the agent to 'run task ID 500' but doesn't know if that task is active or exists. The agent fails and stops, wasting time.
→
Always start by calling list_tasks to verify the script name and check its status first. Then use run_task with confidence.
Overlooking project scope
The user is confused about which set of tasks they are working in, leading them to try running a task from an old, irrelevant project.
→
Call list_projects first. This forces the agent and you to agree on the correct context before listing or creating anything.
Assuming immediate data retrieval
The user asks for scraping results immediately after calling run_task, but the browser needs time to load content, resulting in incomplete or empty data.
→
Use a combination of list_runs and then get_run to poll the status. Don't assume completion; always check the run record first.
When It Fits, When It Doesn't
Use this MCP when your problem involves interacting with a visual web interface, not just an API endpoint. If you need to scrape data that requires clicking through several pages or if the layout matters for testing (like checking element positions), use Browserbear. Don't use it if all the data is already available via a structured API call—that's faster and doesn't require browser overhead. Also, don't rely on it to simply manage files; that’s for dedicated storage tools. Use list_tasks when you need an overview of your scripts, but use run_task only when you are sure the script is ready to execute.
Common Questions About Browserbear MCP
How do I take a screenshot of a specific URL using `take_screenshot`? +
You simply ask your agent to run the tool and provide the full URL. You can also specify custom dimensions (e.g., 1280x720) in the request for precise captures.
What is the difference between `list_tasks` and `list_runs`? +
list_tasks shows you the templates or scripts you have saved (what's possible). list_runs shows you a historical log of every time those tasks actually ran.
Can I manually start an old task using `run_task`? +
Yes. You use run_task and pass the ID of the saved script. If that script needs a dynamic input, you can override it right in your prompt.
How do I delete old data using `delete_run`? +
You call delete_run and provide the specific run ID you want to remove from your history. This is useful for maintaining a clean audit trail.
How do I use `create_task` to set up a new browser automation task? +
You send the necessary parameters to start building the task. The tool validates your input and registers the workflow definition in your account, making it ready for future runs.
What information does `get_account_usage` provide about my API access? +
It pulls detailed metrics showing how much of your quota you've used. This lets you track usage across different projects and manage spending against your set budget.
If a task fails, what details can I get using `get_run`? +
The tool gives you the status of a specific run, including error logs and execution timestamps. You can pinpoint exactly where the automation broke down to debug it.
How do I check which projects are available with `list_projects`? +
It returns a list of all project containers you have set up in Browserbear. This helps organize tasks and ensures you run the automation under the correct scope.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.