Why Third Party AI Security Can't Be Optional

Why Third Party AI Security Can’t Be Optional

The MCP security space is evolving quickly. As AI and machine learning continue to drive innovation, new security challenges are emerging—how do we handle it when an AI agent goes to act in the world? Right now, folks are attempting to solve these issues in a bunch of different methods—embedding security into server runtimes, adding it to traditional API products, or relying on old-school policy databases that flag “bad actions.”

But these methods aren’t built for the complexity and unpredictability of AI behavior. Traditional security frameworks simply aren’t enough for AI systems. AI agents require more tailored validation, especially when their actions can be unpredictable and the impacts far-reaching.

The Need for Customizable Validation

When an AI agent acts in the world, we can’t afford to let it go unchecked. We need a way to validate its actions and ensure they’re safe, wise, and aligned with our specific needs. Static, legacy security methods can’t keep up with the nuances of AI behavior.

The solution lies in customizable, third-party validation. We need a standard that lets us host, configure, and control the validation process ourselves, based on our unique requirements. AI systems can behave in countless (and often shocking) ways, so having the flexibility to tweak and adjust the validation criteria is crucial.

Why We Built Maybe Don’t

This is why we built Maybe Don’t the way we did: configurable, customizable, downloadable, and self-hosted. You control the validation process by choosing the model and the checks that best fit your needs. We provide the rails to perform validation checks, but you can adjust the system to meet your specific security requirements.

Too many failures in the last few years have stemmed from unchecked AI decisions. Maybe Don’t let that happen.

What You Get with Maybe Don’t

Maybe Don’t gives you a downloadable working product right out of the box, and you can tweak it to configure it to meet your unique needs. You get full control over what model is being used for validation, what , allowing you to ensure AI operates within safe and acceptable boundaries.

Conclusion

When AI goes to act on the world it needs robust, customizable validation. We can’t simply hope for the best, and existing systems don’t share our incentives for security. To ensure AI is acting safely, ethically, and in line with our needs, we need a dynamic, third party, validation framework.

That’s why Maybe Don’t exists: to give you full control over AI validation. Maybe Don’t let your AI agents act unchecked.