agent-sandbox

Self-hostable, disposable sandboxes where AI agents run code, with snapshot, rollback, and fork.

You give an agent a sandbox. The agent writes files, runs commands, and streams the output. Before it tries something risky, it takes a snapshot. When the attempt goes wrong, it rolls back in one call, or forks the snapshot into several sandboxes and tries three ideas in parallel. When the agent forgets to clean up, the TTL reaper does it for you.

agent-sandbox is a small Python server with a REST API, a Python SDK, and an MCP server. It runs on any Linux host with Docker, and your code never leaves your infrastructure.

The documentation site has a quickstart, concepts, the architecture, references, and an FAQ.

Install

Install the standalone agent-sandbox executable for your OS and CPU:

curl -fsSL https://raw.githubusercontent.com/superintelligenceco/agent-sandbox/main/install.sh | sh

The script checks the download against the release's SHA256SUMS and installs it into ~/.local/bin. Set AGENT_SANDBOX_VERSION=v0.2.1 to pin a release, or AGENT_SANDBOX_INSTALL=compose to download the Compose file, write an API key, and start the server image instead. Then start the server with AGENT_SANDBOX_API_KEYS=$(openssl rand -hex 24) agent-sandbox serve. Your user needs access to the Docker socket.

Or install the Python package from PyPI. The distribution is sic-agent-sandbox; the import package and the commands keep the agent_sandbox and agent-sandbox names:

pip install "sic-agent-sandbox[server,mcp]"

Each release ships these files:

Verify a downloaded file with gh attestation verify <file> -R superintelligenceco/agent-sandbox.

Run the server with Docker Compose

You need a Linux host with Docker and the Compose plugin. Download the Compose file, set an API key, and start the server:

curl -fsSLO https://github.com/superintelligenceco/agent-sandbox/releases/latest/download/docker-compose.yml
export AGENT_SANDBOX_API_KEY=$(openssl rand -hex 24)
docker compose up -d

The API now listens on http://localhost:8080. Check it with curl localhost:8080/healthz. The Compose file pins the image of its release. Set AGENT_SANDBOX_VERSION to run another tag, AGENT_SANDBOX_PORT to change the host port, and AGENT_SANDBOX_DEFAULT_IMAGE to change the sandbox image. Stop the server and delete its data with docker compose down -v.

To run the image without Compose:

docker run -d --name agent-sandbox -u 0:0 -p 127.0.0.1:8080:8080 \
  -v /var/run/docker.sock:/var/run/docker.sock -v agent-sandbox-data:/data \
  -e AGENT_SANDBOX_API_KEYS="$AGENT_SANDBOX_API_KEY" \
  ghcr.io/superintelligenceco/agent-sandbox:latest

Install the Python SDK and MCP server

pip install "sic-agent-sandbox[mcp]"
agent-sandbox-mcp   # MCP server over stdio

Leave out [mcp] if you only need the SDK, which depends on httpx alone.

Build from source

git clone https://github.com/superintelligenceco/agent-sandbox && cd agent-sandbox
export AGENT_SANDBOX_API_KEY=$(openssl rand -hex 24)
docker compose -f docker-compose.yml -f docker-compose.build.yml up -d --build

Related MCP server: agent-jail-mcp

See it work

This session is a verbatim capture from a Compose stack, with $API set to http://localhost:8080/v1.

$ sb() { curl -s -H "Authorization: Bearer $AGENT_SANDBOX_API_KEY" -H "Content-Type: application/json" "$@"; }

# 1. Create a sandbox (no network, read-only rootfs, non-root user by default).
$ SB=$(sb -X POST $API/sandboxes -d '{"image": "python:3.12-slim", "timeout_seconds": 600}' | jq -r .id); echo $SB
sb_2f10f5a9403f25d0

# 2. Write some code and run it.
$ sb -X PUT "$API/sandboxes/$SB/files?path=app.py" --data-binary 'print(sum(range(10)))' | jq -c .
{"name":"app.py","path":"/workspace/app.py","type":"file","size":21,"modified_at":"2026-09-30T09:56:02.053406Z"}
$ sb -X POST $API/sandboxes/$SB/exec -d '{"command": "python3 app.py && id"}' | jq .
{
  "stdout": "45\nuid=1000 gid=1000 groups=1000\n",
  "stderr": "",
  "exit_code": 0,
  "timed_out": false,
  "truncated": false,
  "duration_ms": 85
}

# 3. Snapshot the working state.
$ SNAP=$(sb -X POST $API/sandboxes/$SB/snapshots -d '{"name": "working"}' | jq -r .id); echo $SNAP
snap_485f667dcf5910ac

# 4. Break something.
$ sb -X POST $API/sandboxes/$SB/exec -d '{"command": "rm -rf /workspace/* && python3 app.py"}' | jq .
{
  "stdout": "",
  "stderr": "python3: can't open file '/workspace/app.py': [Errno 2] No such file or directory\n",
  "exit_code": 2,
  "timed_out": false,
  "truncated": false,
  "duration_ms": 95
}

# 5. Roll back and stream the output of the next command.
$ sb -X POST $API/sandboxes/$SB/rollback -d "{\"snapshot_id\": \"$SNAP\"}" | jq -c "{id, status, source_snapshot_id}"
{"id":"sb_2f10f5a9403f25d0","status":"running","source_snapshot_id":"snap_485f667dcf5910ac"}
$ sb -X POST $API/sandboxes/$SB/exec/stream -d '{"command": "python3 app.py; ls -l"}'
{"type": "stdout", "data": "45\n"}
{"type": "stdout", "data": "total 4\n-rw-r--r--. 1 1000 1000 21 Sep 30 09:56 app.py\n"}
{"type": "exit", "exit_code": 0, "timed_out": false, "duration_ms": 121}

# 6. Clean up.
$ sb -X DELETE -o /dev/null -w "%{http_code}\n" $API/sandboxes/$SB
204

The same thing from Python

pip install sic-agent-sandbox
export AGENT_SANDBOX_URL=http://localhost:8080

from agent_sandbox.client import SandboxClient

with SandboxClient() as client, client.create(image="python:3.12-slim") as sandbox:
    sandbox.write_file("app.py", "print('hello from', __import__('platform').python_version())\n")
    good = sandbox.snapshot("working")
    sandbox.exec("rm app.py")
    sandbox.rollback(good)
    for event in sandbox.exec_stream("python3 app.py"):
        print(event)

Output of examples/quickstart.py, which runs a longer version of this code:

created Sandbox(id='sb_2bc35260898babc9', image='python:3.12-slim', status='running')
run 1: hello from 3.12.13
snapshot snap_bdb4731b7ddb7b93 (10240 bytes)
after rm: exit 2 | python3: can't open file '/workspace/app.py': [Errno 2] No such file or directory
after rollback: hello from 3.12.13
stream: ExecEvent(type='stdout', data='tick 1\n', exit_code=None, timed_out=False, duration_ms=None)
stream: ExecEvent(type='stdout', data='tick 2\n', exit_code=None, timed_out=False, duration_ms=None)
stream: ExecEvent(type='stdout', data='tick 3\n', exit_code=None, timed_out=False, duration_ms=None)
stream: ExecEvent(type='exit', data='', exit_code=0, timed_out=False, duration_ms=641)

examples/parallel_forks.py forks one snapshot into three sandboxes, benchmarks a different implementation in each, and prints the results.

From an MCP client

Install the package with the mcp extra (see Install) and point your MCP client at the agent-sandbox-mcp command. It speaks MCP over stdio.

{
  "mcpServers": {
    "agent-sandbox": {
      "command": "agent-sandbox-mcp",
      "env": {
        "AGENT_SANDBOX_URL": "http://localhost:8080",
        "AGENT_SANDBOX_API_KEY": "replace-with-your-key"
      }
    }
  }
}

The server exposes ten tools: sandbox_create, sandbox_list, sandbox_exec, sandbox_read_file, sandbox_write_file, sandbox_list_files, sandbox_snapshot, sandbox_rollback, sandbox_fork, and sandbox_destroy. Its instructions tell the model to snapshot before risky changes.

Why it exists

Agents that write code need somewhere to run it. Running it on the host is dangerous, and hosted sandbox services mean your code, data, and credentials leave your network. agent-sandbox gives you the useful parts of those services on a machine you control:

• Disposable by default. Every sandbox has a time to live, and the server reaps it when the TTL passes.

• Undo for agents. Snapshot, rollback, and fork are first-class API calls, so an agent can explore without losing a known-good state.

• Small enough to read. About 2,500 lines of Python. You can audit the whole isolation path in an afternoon.

Features

• REST API with an OpenAPI 3.1 spec. FastAPI also serves interactive docs at /docs.

• Create sandboxes from any OCI image, with CPU, memory, process-count, and TTL limits, and network access off or on.

• Run commands to completion, or stream stdout and stderr as NDJSON while they run. Timeouts kill the whole process group.

• Read, write, and list files. Uploads and downloads are raw bytes, so binary files work.

• Snapshot /workspace, roll back to a snapshot, and fork a snapshot into a new sandbox. Snapshots outlive the sandbox they came from.

• TTL reaping, per-server quotas, an image allowlist, and orphan cleanup when the server restarts.

• API key authentication with Authorization: Bearer or X-API-Key.

• Python SDK (agent_sandbox.client, depends only on httpx) and an MCP server.

• A Backend interface, so other isolation technologies can plug in. Docker is the backend that ships today.

API overview

Every /v1 route needs an API key. The OpenAPI spec holds the full request and response schemas.

Errors share one shape: {"error": {"code": "not_found", "message": "..."}}.

Configuration

You configure the server with environment variables. The most common ones:

config.py lists every setting.

Security model

Read this section before you expose the server to anything you don't trust.

What a sandbox gets by default

Each sandbox is one Docker container plus one named volume mounted at /workspace. The container runs with:

• A non-root user (1000:1000), and HOME=/workspace.

• Every Linux capability dropped and no-new-privileges set.

• A read-only root filesystem. Only /workspace (a volume) and /tmp (a size-limited nosuid,nodev tmpfs) are writable.

• No network interface except loopback. When you request network: true, the sandbox joins a dedicated bridge network with inter-container traffic disabled.

• Memory, CPU, and process-count limits, with swap disabled.

• A private IPC namespace and an init process that reaps zombies.

• A fixed hostname and no host mounts other than its own volume.

The integration tests check each of these properties against a real Docker daemon on every CI run.

Honest limits

• Containers are not virtual machines. Every sandbox shares the host kernel. A kernel vulnerability can let code escape the container. If you run code from untrusted users, not only from your own agents, use a stronger runtime such as gVisor, or put the whole host inside a VM you're willing to lose.

• The server controls Docker. It needs the Docker socket, and access to the Docker socket is equivalent to root on the host. Treat the API key as a root credential, keep the port on localhost or behind TLS, and consider a Docker socket proxy that allows only the container, volume, image, network, and exec endpoints.

• Network access is coarse. network: true means outbound access to wherever the host can reach, which can include your LAN and cloud metadata endpoints. There's no egress allowlist yet. Leave networking off unless the task needs it, or block those ranges on the host.

• Snapshots cover /workspace only. Snapshots don't capture memory, running processes, /tmp, or changes to the root filesystem when you turn off read_only_rootfs. Rollback replaces the container, so all of that resets.

• Limits aren't complete. Disk use inside /workspace has no quota on most Docker storage drivers, and snapshot size has a server-side cap (AGENT_SANDBOX_MAX_SNAPSHOT_BYTES) but no per-key budget.

• API keys are flat. Every key can see and control every sandbox. There are no per-key namespaces yet.

Report vulnerabilities as described in SECURITY.md.

Architecture

flowchart LR
    subgraph Clients
        A[Agent or app] -->|Python SDK| API
        M[MCP client] -->|stdio| MCP[agent-sandbox-mcp]
        MCP -->|HTTP| API
        C[curl] -->|HTTP| API
    end

    subgraph Server["agent-sandbox server"]
        API[FastAPI routes<br/>auth, validation, NDJSON streaming]
        MGR[SandboxManager<br/>quotas, TTL reaper, snapshots]
        STORE[(data dir<br/>records + snapshot tarballs)]
        IF{{Backend interface}}
        API --> MGR
        MGR --> STORE
        MGR --> IF
    end

    IF --> DOCKER[DockerBackend<br/>Docker Engine API]
    IF -.-> FC[Firecracker<br/>roadmap]
    IF -.-> GV[gVisor runtime<br/>roadmap]

    DOCKER --> S1[sandbox container<br/>+ workspace volume]
    DOCKER --> S2[sandbox container<br/>+ workspace volume]

• API layer (api.py) validates requests with Pydantic, checks the API key, and maps errors to HTTP status codes.

• Manager (manager.py) owns IDs, quotas, TTLs, locking, and snapshot storage. It persists sandbox records so a restarted server picks up its sandboxes and removes orphans.

• Backend (backends/base.py) is the interface an isolation technology implements: create, destroy, exec, file I/O, and workspace export and import as tar streams.

• Docker backend (backends/docker.py) implements that interface with hardened containers.

A snapshot is a tar of /workspace stored in the data directory. Rollback destroys the container, creates a fresh one with the same spec, and extracts the tar into the new workspace. Fork does the same into a new sandbox ID.

Development

Open the repository in a GitHub Codespace, or in the dev container in .devcontainer/, to get Python, Docker, and every dependency installed. On your own machine:

make setup            # create .venv and install the dev and docs extras
. .venv/bin/activate
pre-commit install    # run the CI linters on every commit
make lint typecheck test
make test-integration # needs a Docker daemon you can reach
make docs             # build the documentation site into site/
agent-sandbox openapi -o docs/openapi.json   # after any API change

Run make to list every target. Run the server from source with AGENT_SANDBOX_API_KEYS=<key> agent-sandbox serve.

Roadmap

These items are plans, not features. Nothing here ships today.

• gVisor. AGENT_SANDBOX_DOCKER_RUNTIME=runsc already passes the runtime to Docker, but the project doesn't test or support it yet. The goal is a CI job that runs the integration suite under gVisor.

• Firecracker. A backend that runs each sandbox in a microVM, with snapshots of the full VM, including memory.

• Egress control. Per-sandbox allowlists for outbound network traffic.

• Multi-tenant keys. Sandboxes scoped to the API key that created them, with per-key quotas.

• TypeScript SDK.

• Workspace quotas on storage drivers that support them.

Contributing

Read CONTRIBUTING.md to set up a development environment and open a pull request. Everyone who takes part agrees to the code of conduct.

License

Apache-2.0. See LICENSE.