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Provide AI assistants controlled, tiered access to environment variables.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "envibe-mcp" yet — see the docs or source repo.
List the environment variables currently accessible, and show each variable's access level and visible information scope.
Returns a list of environment variables and explains which are readable, placeholder-only, schema-only, or hidden.
Get the current access result for DATABASE_URL and explain whether its value is readable, whether it only returns placeholder information, and its variable description.
Returns the content visible under the current permission level, along with its purpose or description.
Set APP_ENV to production and confirm whether the update succeeds; if current permissions do not allow changes, state that directly.
Returns the update result, confirming success or explaining permission or access-level restrictions on failure.
Developers or DevOps engineers can let an AI assistant read selected environment variables while limiting sensitive exposure through read-only, placeholder, or hidden access levels.
When application configuration goes wrong, teams can let AI list variables, inspect descriptions, and read allowed values to identify missing or incorrect settings.
When write access is allowed, users can set or update specific environment variables through AI while keeping tiered access control in place.
It is an MCP server for envibe that gives AI assistants controlled access to environment variables. It supports listing, getting, setting, and describing variables, with five access levels.
The provided description mentions five levels: full, read-only, placeholder, schema-only, and hidden. They control how much of an environment variable an AI can see or operate on.
The current materials do not provide installation steps, runtime requirements, or key configuration details. For more information, see the source repository.
Safely manage Python environments and dependencies within a project workspace.
Give AI full visibility into your local development environment for faster troubleshooting.
Manage Vibe Kanban tasks, sessions, and queues inside AI coding workflows.
Manage MCP server configurations with listing, toggling, and version control.
Upload Postman assets via MCP and run API tests with managed results.
Use one MCP server for filesystem, database, web, and system operations.