Envibe FAQs

Question 1

What are the MCP tools provided by Envibe for AI interaction?

Accepted Answer

Envibe includes powerful MCP tools like `env_list` (list visible variables), `env_get` (get a variable), `env_set` (set a variable with 'full' access), `env_describe` (get detailed info), and `env_check_required` (check missing variables).

Question 2

What is Envibe and how does it secure my .env data?

Accepted Answer

Envibe is a critical permission layer that provides granular AI access control for your environment variables, securing sensitive `.env` data. It blocks direct AI access to the raw `.env` file and creates a filtered `.env.ai` for safe interaction.

Question 3

What access levels does Envibe offer for AI agents?

Accepted Answer

Envibe provides five granular access levels: `full` (read/write), `read-only`, `placeholder` (AI sees variable name only), `schema-only` (AI sees format hints), and `hidden` (AI sees nothing).

Question 4

How does Envibe improve AI interactions with environment variables?

Accepted Answer

It offers better error messages when access is denied, provides format hints (e.g., URL, key, number) to guide AI, and allows checking for required variables, ensuring smoother and more secure AI operations.

Question 5

Is Envibe easy to integrate with existing AI tools?

Accepted Answer

Yes, Envibe is designed for easy integration with AI tools supporting MCP (e.g., Claude, VS Code/Cursor). On first run, it automatically generates `.env.manifest.yaml` and `.env.ai` from your `.env.example`.

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Key Features

Use Cases

Key Features

Use Cases