Your agent, deployed

Turn your local agent to a deployed service with one command
Superserve handles the infrastructure so you don't have to

Built for agents that use the terminal, run code, browse the web and manage files

OpenAI
Claude
LangChain
Mastra
Pydantic AI
Agno

Agents need more than sandboxes

Sandboxes run agent code in isolation. But isolation alone isn’t enough for production agents.

research-agent
progress0%
session limit24:00:00

Sessions

Production agents run for hours or days. They need isolated sessions without caps or surprise shutdowns.

agent workspace
0 items
storage: ephemeral-2 KB

Workspaces

Every agent needs a home. A persistent filesystem where files and progress survive restarts.

integration.ts

Streaming SDK

Once your agent runs in isolation, it needs a way to talk to your app. Responses, tool calls, and status updates in real time.

Superserve provides this layer

Runtime for agents that do real work

From local to production

Build your agent locally, deploy to our cloud or your VPC with a single command

main.py
local
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Terminal
zsh
$
Sessions
sess-01
waiting
a7f3k
sess-02
waiting
b2m8p
sess-03
waiting
c5n1q
sess-04
waiting
d9j4r

Why Superserve?

Skip the infrastructure work, ship your agent

Sandbox platforms
Superserve
Focus
Isolated execution
Hosted agents
Sessions
Manual
Managed
Workspaces
Ephemeral
Persistent
App integration
DIY
Streaming SDK
Agent deployment
DIY
superserve deploy

FAQ

Common questions

Open Source

Built in the open

Superserve is open source. Contribute, request features, or add support for your favorite agent SDK.

Your agent, production-ready
in minutes

One command. No infrastructure to manage.

Sandboxed executionPersistent workspacesStreaming SDKOne-command deploy