> For the complete documentation index, see [llms.txt](https://docs.firefly.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.firefly.ai/detailed-guides/workspace-importer.md). # Workspace Importer Firefly Workspace Importer is a lightweight, open-source CLI tool that bulk-imports existing Terraform repositories into Firefly as Workspaces and Projects. Rather than creating workspaces one at a time through the UI, teams onboarding a large number of repositories can point the importer at their VCS integration and let it scan every repository for Terraform directories, then create the matching Firefly Workspaces — and, optionally, a mirrored Project hierarchy — in a single run. Because the tool authenticates only to Firefly's API and reuses the VCS integration you've already configured in Firefly, no GitHub, GitLab, or Bitbucket credentials ever need to be shared with it. It supports a dry-run mode to preview exactly what will be created, an interactive review step before anything is written, and is safe to re-run as new repositories are added. The importer is distributed as a single-file Python script or a distroless Docker image, making it easy to run locally or as part of a CI pipeline during onboarding. For setup instructions, configuration options, and troubleshooting, see the [Workspace Importer repository](https://github.com/gofireflyio/firefly-workspace-importer) on GitHub. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.firefly.ai/detailed-guides/workspace-importer.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.