---
title: "Baponi"
description: "Sandboxed code execution for AI agents. No container lifecycle, no idle billing, sub-20ms overhead. Tears down after every call, resumes where you left off."
url: https://baponi.ai/
---
# Run code, not containers.

Tears down after every call. Resumes where you left off in under 20ms, as if it never stopped. No zombies, no idle billing.

[Get Started Free](https://console.baponi.ai) [Read the Docs](https://baponi.ai/docs.md)

```
$ curl -X POST https://api.baponi.ai/v1/sandbox/execute \
  -H "Authorization: Bearer sk-..." \
  -d '{
    "language": "python",
    "code": "print(\'Hello World!\')"
  }'
```

```
# Response
{ "stdout": "Hello World!\n", "exit_code": 0 }
```

```
{
  "mcpServers": {
    "baponi": {
      "url": "https://api.baponi.ai/mcp",
      "headers": {
        "Authorization": "Bearer sk-..."
      }
    }
  }
}
```

Claude Desktop, Cursor, Windsurf, and any MCP client.

## No create(). No close(). Just execute().

Other sandbox SDKs make you manage container lifecycle. With Baponi, your API key already knows the image, resources, storage, and credentials. You just send code.

```
# Typical sandbox SDK
sandbox = provider.create()          # boot container
sandbox.upload("data.csv", "/tmp/")  # move data in
sandbox.run("pip install pandas")    # install deps
result = sandbox.run(code)           # your code
files = sandbox.download("/output/") # move data out
sandbox.close()                      # cleanup

# Forgot close()? Zombie container.
# Timeout? State is gone.
# LLM thinking? Still billing.
```

```
$ curl -X POST https://api.baponi.ai/v1/sandbox/execute \
  -H "Authorization: Bearer sk-..." \
  -d '{"code": "print(42)"}'
```

```
result = baponi.execute(code)

# LangChain, DeepAgent, Anthropic, OpenAI,
# Gemini, CrewAI, and any MCP client.
```

### Stateful when you need it.

Add a `thread_id` to persist the sandbox environment between calls. Installed packages and working files are saved automatically.

-   **Zero idle cost.** Nothing runs until you call again. No billing between calls.
-   **Configurable retention.** 24 hours, 7 days, 30 days, or forever.

[Learn How It Works](https://baponi.ai/docs/getting-started/how-it-works.md)

```
# Call 1: set up the environment
client.execute(
    code="pip install pandas scikit-learn",
    language="bash",
    thread_id="analysis-x8k2",
)

# Hours later, zero cost in between
client.execute(
    code="import pandas; print(pandas.__version__)",
    language="python",
    thread_id="analysis-x8k2",
)
# Nothing ran between calls. Same environment.
```

## Mount data, don't copy it.

Other sandboxes hold your data hostage. Use their volumes or build your own sync pipeline. With Baponi, mount your S3 or GCS bucket as a local directory. Every file is there on spin-up. Writes go straight to your bucket. Read-only or read-write, your rules.

-   **Single source of truth.** Your bucket is THE storage. No duplicated data.
-   **Read-only enforcement.** Enforced at the kernel level, not an application permission check.
-   **Sub-path scoping.** Mount `users/user-123/` for per-tenant isolation.

### Bring Your Own Bucket

Unlimited

Mount your own S3, GCS, or Azure Blob. Data never leaves your cloud. Sub-path scoping for multi-tenant isolation. Read-only mode available.

AWS S3 GCS Azure Blob S3-compatible

### Managed Volumes

10 GB free

Baponi-hosted persistent storage. Attach volumes to your agents for datasets, models, and output files. No cloud credentials needed.

## Everything your agents need. Nothing they don't.

### Sub-20ms. Always.

Under 20ms on every single call. No VM boot. No pod spin-up. No warm-node lottery. Not just when conditions are right.

### Network Control

Block all outbound access by default, or open it up when your agent needs internet. Per-sandbox network policies, enforced at the kernel level.

### Custom Runtimes

Bring your own container image pre-loaded with your company's packages and internal tools. Your AI agents work with your stack, not a generic sandbox.

### Stateful Without Running

State persists between calls, but nothing runs. No idle billing, no timeouts, no orphans. Pick up where you left off, minutes or days later.

### MCP + REST + Python SDK

Full MCP support. Direct REST API. Or pip install. 2 lines to run code from any AI agent.

### Your Cloud. Your VPC.

The entire platform deploys inside your infrastructure. Built from day one for self-hosted enterprise. Or start with our managed cloud and move when you're ready.

## One place to manage which agents access what

Configure credentials once, assign per agent. CLI tools like psql, git, bq and any code that needs those credentials just works. No more custom tools.

### Databases

PostgreSQL MySQL BigQuery MongoDB Redis

### Cloud Storage

AWS S3 Google Cloud Storage Azure Blob S3-compatible

### APIs & SCM

GitHub GitLab Slack Jira

```
# Credentials injected transparently. CLI tools and code just work.
$ psql -c "SELECT count(*) FROM orders"
 count
-------
 42891

$ git clone https://github.com/acme/private-repo.git
Cloning into 'private-repo'... done.

$ python3 -c "
import psycopg2
conn = psycopg2.connect('dbname=analytics')
cur = conn.cursor()
cur.execute('SELECT sum(revenue) FROM sales')
print(cur.fetchone()[0])"
1284930
```

### Your agents already know how to use these tools.

LLMs have seen millions of examples of psql, git, and bq in their training data. Baponi makes it work in practice by handling the credentials.

-   01 Configure connector credentials in the console
-   02 Associate connectors with an API key
-   03 Agent runs code. Credentials injected as native config files.

[Explore Connectors](https://baponi.ai/features.md#connectors)

<20ms

Cold start overhead

$0

Idle billing

1K

Free credits/mo

$0

To get started

## Ready to get started?

1,000 free credits/month. Unlimited seats. No credit card required.

[Start Building Free](https://console.baponi.ai) [Talk to Our Security Engineers](https://calendly.com/baponi/baponi-enterprise)

## More from Baponi

- Product: [Features](https://baponi.ai/features) · [Pricing](https://baponi.ai/pricing) · [Enterprise](https://baponi.ai/enterprise) · [Baponi vs E2B](https://baponi.ai/compare/vs-e2b) · [Baponi vs Daytona](https://baponi.ai/compare/vs-daytona) · [Baponi vs Modal](https://baponi.ai/compare/vs-modal) · [Baponi vs Vercel Sandbox](https://baponi.ai/compare/vs-vercel)
- Developers: [Documentation](https://baponi.ai/docs) · [API Reference](https://baponi.ai/docs/api/overview)
- Trust: [Trust Center](https://baponi.ai/trust)
- Site index: [llms.txt](https://baponi.ai/llms.txt) · [llms-full.txt](https://baponi.ai/llms-full.txt)

```json
{"@context":"https://schema.org","@type":"WebSite","name":"Baponi","url":"https://baponi.ai","description":"Sandboxed code execution for AI agents."}
```