Integrations

Agent frameworks

Your agent keeps its framework. Its shell commands, file edits and code run in a Promigence sandbox.

• LangChain

  langchain-promigence, PyPI

  Use a Promigence sandbox as the backend of a LangChain Deep Agent, so the agent's shell commands and file edits happen in the sandbox. The same package adds a promigence sandbox provider to deepagents-code.

• OOpenAI Agents SDK

  promigence-openai-agents, PyPI

  Give an OpenAI Agents SDK SandboxAgent a Promigence sandbox, so its shell and file tools run there instead of on your machine. Your agent code stays the same; only the client you pass in changes.

• Claude Agent SDK

  promigence-claude-agent-sdk, npm

  Keep the Claude Agent SDK loop in your own process and run Claude Code itself inside a Promigence sandbox. Anything the agent edits, installs or deletes stays in the sandbox.

• Vercel AI SDK

  promigence-ai-sdk-sandbox, npm

  Pass a Promigence sandbox to the Vercel AI SDK as experimental_sandbox, or to bash-tool. The commands your tools run and the files they touch stay in the sandbox, away from your server.

• Google ADK

  promigence-google-adk, PyPI

  Point a Google ADK agent's environment tools, or its code executor, at a Promigence sandbox. The agent's commands and the code its model writes then run there instead of on the machine serving the agent.

• SStrands Agents

  strands-promigence, PyPI

  A Strands agent handed a Promigence sandbox runs its shell and file-editor tools there. Output streams back while a command is still running, so a line a long test run prints early reaches the agent well before the run ends.

• Claude Managed Agents

  promigence-claude-managed-agents, PyPI

  Run the workers of a Claude Managed Agents self-hosted environment on Promigence sandboxes, as a pool you size and give a spend cap. The sessions on that environment are served from the pool.

Evals and benchmarks

Each sample, trial or task instance gets its own sandbox, and many run at once.

• IInspect

  inspect-promigence, PyPI

  Use sandbox="promigence" in Inspect and every sample gets its own cloud sandbox, with no Docker daemon on your machine. Tasks written for Docker, from a Dockerfile or a single-service compose file, run unchanged.

• HHarbor

  promigence-harbor, PyPI

  Select Promigence in Harbor with one flag. Terminal-Bench and other Harbor tasks then run in cloud sandboxes, each trial in its own copy of the task's environment and many trials at once, with no change to Harbor.

• mmini-swe-agent

  promigence-mini-swe-agent, PyPI

  Run mini-swe-agent's SWE-bench instances on Promigence sandboxes. Nothing in mini-swe-agent changes: you name the Promigence environment class on the command line, and each instance runs its commands in its own sandbox while many workers run at once.

Building your own harness? Start sandboxes from the Python SDK, the TypeScript SDK or the REST API. The guides go step by step.