Mirage

Mirage provides a unified virtual filesystem designed for AI agents, allowing them to interact with a variety of data sources, services, and tools through a single abstraction layer. By presenting disparate backends such as S3, Google Drive, GitHub, Notion, Redis, and Postgres as mountable resources under one root, Mirage enables agents to use familiar bash commands to read, write, and pipe data across heterogeneous systems as if they were local files. h5.

A key feature of Mirage is its support for versioned snapshots and rollbacks, similar to git, allowing users to snapshot the state of a workspace, clone it for parallel runs, and revert to previous versions with a single API call. tar files, enabling agent runs to move seamlessly across hosts without requiring restarts. Mirage also incorporates a two-layer cache system, minimizing redundant network calls by caching repeated reads at both the index and file level, which helps maintain performance and cost efficiency during agent operations.

Mirage is delivered as open-source software, with SDKs available for Python and TypeScript, as well as a CLI. It can be embedded directly into FastAPI, Express, browser applications, or any asynchronous runtime. The platform offers adapters for integration with AI agent frameworks such as OpenAI Agents SDK, Vercel AI SDK, LangChain, Pydantic AI, CAMEL, Mastra, and OpenHands. Deployment is supported across Node, servers, CLIs, browsers, and edge environments, with resources mountable from a wide range of cloud services, messaging platforms, and databases.

By abstracting diverse backends into a single virtual filesystem with a bash interface, Mirage streamlines agent workflows and reduces the need for multiple SDKs or custom connectors. Its open-source licensing and broad compatibility make it suitable for developers building or orchestrating AI agents that require seamless access to varied data and service backends.