Apache-2.0 unified virtual filesystem for AI agents — mounts ~50 services (S3, Slack, Gmail, Redis...) as one bash-friendly tree, connecting to DeepSeek Harness via native adapter, installable plugin, MCP, or FUSE.
DSH integration
Compatible
Author-claimed
Safety audit
Unaudited
Last verified
2026-08-21
License
Apache-2.0
01What can it help you accomplish?
Give DeepSeek Harness bash-level access to S3, Google Drive, Slack, Gmail, Redis and ~50 more services as one virtual filesystem
A single mounted workspace where read, grep and pipe commands sweep every backend out of the box, with zero new vocabulary
Developers running DeepSeek Harness (dsh) who want their agent to query real cloud and SaaS data without wiring up separate SDKs or MCP servers
Compose cross-service pipelines and keep agent runs portable on DeepSeek Harness
bash pipelines that span backends (e.g. run a script stored in Slack and file the report into Redis), plus clone / snapshot / version of portable workspaces that move between machines
Teams building agent workflows on DeepSeek Harness that need reproducible, portable workspaces across services
02How to install into DeepSeek Harness
Prerequisites
- Python ≥ 3.11 for the `mirage-ai` package and the `mirage` CLI
- Node.js ≥ 20 for the TypeScript SDK
- macOS or Linux (FUSE-based mounts require platform support)
Installation steps
- 01
Python: run `uv add mirage-ai` — installs the `mirage` library and the `mirage` CLI binary
- 02
TypeScript: run `npm install @struktoai/mirage-node` (Node.js servers and CLIs), `npm install @struktoai/mirage-browser` (browser / edge runtimes), and optionally `npm install @struktoai/mirage-agents` (OpenAI / Vercel AI / LangChain / Mastra adapters)
$ npm install @struktoai/mirage-node
- 03
CLI: run `curl -fsSL https://strukto.ai/mirage/install.sh | sh`, or `npm install -g @struktoai/mirage-cli`, or `uvx mirage-ai`, or `npx @struktoai/mirage-cli`
$ curl -fsSL https://strukto.ai/mirage/install.sh | sh
Verify the integration
Not specified by the author
03DSH integration and capability boundaries
Used inside DeepSeek Harness as a coding-agent tool layer via native adapter, installable plugin, MCP, or FUSE mount
Unified virtual filesystem with ~50 built-in backends
S3 / R2 / GCS / Supabase, Gmail / GDrive / GDocs / GSheets / GSlides, GitHub / Linear / Notion / Trello, Slack / Discord / Email, MongoDB / Postgres / LanceDB / Qdrant, Redis, SSH, RAM, Disk→one filesystem tree under a single root, readable with standard bash semantics (read, grep, pipe)
reads and writes are executed against the mounted remote services using your own credentials/tokensPortable workspaces (clone / snapshot / version)
a configured Mirage workspace→snapshot archives (e.g. demo.tar) that can be loaded on another machine to restore the workspace
snapshot files are written to diskTwo-layer cache for remote backends
repeated reads against remote backends→index cache (listings/metadata, default TTL 10 minutes) and file cache (object bytes, default 512 MB) served from local state
cache state is held in-process RAM by default; an optional Redis store shares cache state across workers, processes, and machinesEmbeddable Python and TypeScript SDKs
a Python ≥ 3.11 or Node.js ≥ 20 application→workspaces running in-process inside FastAPI, Express, browser apps, or any async runtime — no separate process required
04Who is it for? When not to use it?
Good for
- Developers running DeepSeek Harness (dsh) who want their agent to query real cloud and SaaS data without wiring up separate SDKs or MCP servers
- Teams building agent workflows on DeepSeek Harness that need reproducible, portable workspaces across services
Not for
- Mirage targets macOS or Linux; FUSE-based mounts additionally require platform support, so FUSE mounting is not guaranteed on every machine.
- Mounted remote backends (Slack, S3, Gmail, Redis, ...) are reached over the network with your own credentials — e.g. a Slack bot token is passed in the resource config — so writes can mutate the underlying services.
05Compatibility, maintenance and safety notes
- Mirage targets macOS or Linux; FUSE-based mounts additionally require platform support, so FUSE mounting is not guaranteed on every machine.
- The Python SDK and CLI require Python ≥ 3.11, and the TypeScript SDK requires Node.js ≥ 20 — older runtimes cannot run Mirage.
- Mounted remote backends (Slack, S3, Gmail, Redis, ...) are reached over the network with your own credentials — e.g. a Slack bot token is passed in the resource config — so writes can mutate the underlying services.
Apache-2.0 · actively maintained (latest release v0.0.5, 2026-08-15)
06Frequently asked questions
How does Mirage connect to DeepSeek Harness?
DeepSeek Harness is listed among Mirage's official coding-agent integrations. You connect through a native adapter, an installable plugin, MCP, or a FUSE mount, and there is a dedicated DeepSeek Harness quickstart in the Mirage docs (docs.mirage.strukto.ai/typescript/agents/dsh).
Is the integration native or MCP?
Both paths exist: coding agents connect through native adapters and installable plugins on one side, or MCP and FUSE on the other — pick whichever fits your DeepSeek Harness workflow.
What do I need installed first?
Python ≥ 3.11 for the `mirage-ai` package and the `mirage` CLI, Node.js ≥ 20 for the TypeScript SDK, and macOS or Linux if you want FUSE-based mounts (which require platform support).
Which services can it mount?
Around 50 built-in backends: RAM, Disk, Redis, S3 / R2 / OCI / Supabase / GCS, Gmail / GDrive / GDocs / GSheets / GSlides, GitHub / Linear / Notion / Trello, Slack / Discord / Email, MongoDB / GridFS / Postgres / LanceDB / Qdrant, SSH, and more — all mounted side-by-side under a single root.
Where do reads and writes go?
Commands run against the mounted backends: remote services are reached over the network with your own credentials (e.g. a Slack bot token), while a two-layer cache — index plus file, in-process RAM by default, optionally Redis — keeps repeated reads local instead of hitting the network.
07Related DSH workflows
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08Data and sources
**Agent integrations:** OpenAI Agents SDK, Vercel AI SDK, LangChain, Pydantic AI, CAMEL, and OpenHands via the SDKs; cod…
| Coding agents | [Claude Code](https://docs.mirage.strukto.ai/python/agents/claude-code), [Codex](https://docs.mirage.s…
This page is generated from the project’s public documentation, repository metadata and a structured parse of DSH Plugins; last verified on 2026-08-21. Found an error? Submit a correction.
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