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let your own AI create and run e2e tests via mcp

Build fast with AI and test just as effortlessly. Octomind turns natural language prompts from your AI powered interface to end-to-end tests, runs them, analyzes failures, and autofixes issues - so your code doesn’t just vibe, it thrives.

how does MCP integration for testing work?

The Model Context Protocol (MCP) opens the door to limitless integration - connecting your favourite LLM with an endless variety of tools. The magic begins when your agent explores any source you choose, generates a wide range of test case ideas, and seamlessly hands them off to the Octomind agent to bring them to life.

You’ll never want to go back to the old way of working.

ready to give it a try?

Sign up for free and follow the simple steps to integrate the Octomind MCP server with your preferred client.

Popular options like Cursor, Windsurf, and Claude Desktop already support MCP making it super easy to get started.

Try for free! Book a demo

where mcp shines

some end-to-end testing examples to start with
generate & run tests from your IDE agent
Bring Octomind right into your agent-powered IDE and simply ask the agent to suggest both positive and negative test scenarios. It can describe them in plain natural language. Your agent can now directly trigger test generation in Octomind to turn the proposals into automated tests. 
diagram how Octomind tests are created using Cursor via MCP
use your data as context for the agent to build tests from  
With MCP, any source your agent can access becomes fair game - whether it’s a CSV file from  test management, user facing documentation, meeting notes from the last QA standup, a Jira ticket or just about anything else. If your agent can interpret the content and spot opportunities for testing, it can suggest meaningful test cases.  With Octomind, you can turn those ideas into actual test code quickly.
diagram how Octomind tests are created from pdf using Claude Decktop via MCP
send test results to your mcp connected tools
It also works the other way round. Ask your agent to provide you with a management summary of the last 5 test reports and to post it to a specific Slack channel. Or have your agent analize critical failures to understand where to focus on.
diagram - how Octomind tests results are interpreted by Claude decktop and transferred to Slack via MCP

playwright MCP vs. octomind MCP  

What is the difference between a Playwright MCP and Octomind MCP implementation?

Playwright MCP

Use your LLM to remote control your browser with Microsoft Playwright MCP.
screenshot of the Playwright MCP use for browser automation

Octomind MCP

Convert anything into automated test cases with a single prompt with Octomind MCP.
screenshot of Octomind MCP use for test automation

blogtopus: on Playwright, end-to-end tests and AI

50% developer rants, 50% tech news commentary, 100% cephalopod opinions on all things software. It's worth the read.  Guaranteed.
April 2, 2025
Marc Mengler

My MCP vision for Octomind

Last week’s open-sourcing of our MCP implementation is our contribution to the ecosystem. This week we are launching on Product Hunt. Let’s turn testing from afterthought into a first-class citizen together.
AI agents
features
February 13, 2024
Daniel Rödler

AI doesn’t belong to test runtime

Not all AI in e2e testing is created equal. To deploy AI to testing successfully, you have to address concerns of brittleness, interpretability, and clunkiness. Mitigation strategies depend on the testing stage.
testing
generative AI
LLMs
January 31, 2025
Daniel Draper

Testing is more about setup than scripts

Test automation was never just the problem of creating scripts, but a challenge of proper setup and context. Autonomous testing tools should look at test automation as a whole and go beyond simple scripting to be useful.
testing
automation
Try the easier way to automate end-to-end testing. Browse our docs at your own pace or request a personalized demo, if you need to talk to our devs. Or just start for free, today.
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