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Mount a Supermemory container inside a Daytona sandbox so your agent can read and write memory using standard filesystem commands.
Daytona sandboxes currently cannot reach api.supermemory.ai from their datacenter IPs. The SMFS binary still installs (we download it directly from GitHub Releases), the FUSE mount still starts, and pip install claude-agent-sdk still works — but the runtime sync to Supermemory fails. We’re working with Daytona to resolve this. In the meantime, use E2B or a self-hosted mount.

How it works

There are two ways to wire SMFS into a Daytona sandbox — pick the one that fits your architecture.

Agent inside the sandbox

The agent process runs inside the sandbox and accesses the SMFS mount directly.

Agent outside the sandbox

The agent runs in your orchestrating code and executes commands inside the sandbox remotely.

Prerequisites


Install SMFS in a Daytona sandbox

Both patterns below run the same setup snippet inside the sandbox before mounting. Daytona can’t reach smfs.ai, so we download the binary directly from GitHub Releases and add ~/.local/bin to PATH.

Pattern A: Agent inside the sandbox

Agent code

agent.py

Orchestration

run.py

Pattern B: Agent outside the sandbox

The agent runs in your server process and executes commands inside the sandbox remotely via sandbox.process.exec().
run.py

Tips

  • FUSE is available in Daytona sandboxes but user_allow_other needs to be added to /etc/fuse.conf
  • We invoke SMFS as $HOME/.local/bin/smfs in the examples because Daytona’s default zsh PATH doesn’t include ~/.local/bin. Alternatively, prepend it once with export PATH=$HOME/.local/bin:$PATH
  • Use pip install claude-agent-sdk to install the agent SDK (PyPI is reachable)