Get started with Flint AI Platform

Flint AI Platform gives you a few ways to start, and they answer different questions. Start with Discover to learn what agents you have. Choose Evaluate to attack an agent and see how it holds up. Choose Runtime to watch and protect agents already in production. Most teams do Discover first, since it needs no changes to running code.

Discover your agents

Add a GitHub Action to build an inventory of the agents in your repositories, along with the models, tools, and MCP servers behind them.

Evaluate your agents

Connect an agent, attack it with hostile prompts, and score how well it holds up before it reaches your users.

Monitor your agents at runtime

Wrap your LLM client with the Python SDK to capture live sessions and enforce guardrails.

What each one needs

	Discover	Evaluate	Runtime
You provide	A GitHub repository with Python agent code	An agent Flint can reach over HTTP	A running agent you can change
You install	A GitHub Action	Nothing, you configure it in the Platform	The Flint AI Python SDK
You get	An agent inventory and the issues to address	A score for how the agent holds up under attack	Live traces and enforced guardrails

All of them need a Flint AI API key. Discovery also needs an API key from your own LLM provider, since the scan uses a model to analyze your code and that inference is billed to you. Google Gemini’s free tier is enough to try it. Evaluation needs no model-provider key of your own, because Flint supplies the attacker and judge models.