How to integrate E2b MCP with Pydantic AI

This guide walks you through connecting E2b to Pydantic AI using the Composio tool router. By the end, you'll have a working E2b agent that can run a python script to analyze csv data, execute javascript code to validate user input, start a sandbox and list installed packages through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a E2b account through Composio's E2b MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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E2b is an open-source platform for running code in secure, sandboxed environments. It enables safe multi-language code execution for AI-powered apps.

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Introduction

This guide walks you through connecting E2b to Pydantic AI using the Composio tool router. By the end, you'll have a working E2b agent that can run a python script to analyze csv data, execute javascript code to validate user input, start a sandbox and list installed packages through natural language commands.

This guide will help you understand how to give your Pydantic AI agent real control over a E2b account through Composio's E2b MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate E2b with

ChatGPTOpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenCodeCursorVS CodeOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for E2b
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your E2b workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

What is the E2b MCP server, and what's possible with it?

The E2b MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your E2b account. It provides structured and secure access so your agent can perform E2b operations on your behalf.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account with an active API key
  • Basic familiarity with Python and async programming
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

bash
pip install composio pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like E2b
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs
5

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to E2b
  • MCPServerStreamableHTTP connects to the E2b MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for E2b
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["e2b"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
What's happening:
  • We're creating a Tool Router session that gives your agent access to E2b tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
e2b_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[e2b_mcp],
    instructions=(
        "You are a E2b assistant. Use E2b tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the E2b endpoint
  • The agent uses GPT-5 to interpret user commands and perform E2b operations
  • The instructions field defines the agent's role and behavior
8

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with E2b.\n")

while True:
    user_input = input("You: ").strip()
    if user_input.lower() in {"exit", "quit", "bye"}:
        print("\nGoodbye!")
        break
    if not user_input:
        continue

    print("\nAgent is thinking...\n", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • E2b API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

Here's the complete code to get you started with E2b and Pydantic AI:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for E2b
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["e2b"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    e2b_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[e2b_mcp],
        instructions=(
            "You are a E2b assistant. Use E2b tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with E2b.\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "bye"}:
            print("\nGoodbye!")
            break
        if not user_input:
            continue

        print("\nAgent is thinking...\n", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've built a Pydantic AI agent that can interact with E2b through Composio's Tool Router. With this setup, your agent can perform real E2b actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + E2b for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
TOOLS

Supported Tools

Every E2b action and event your agent gets out of the box.

Connect to Sandbox

Tool to connect to an existing E2B sandbox and retrieve its details.

Create Template

Tool to create a new E2B template with specified configuration.

Create Webhook

Tool to register a new webhook to receive sandbox lifecycle events for the team.

Delete Sandbox

Tool to terminate and permanently delete a running E2B sandbox instance.

Delete Webhook

Tool to unregister a webhook and stop receiving lifecycle events.

Check API Health

Tool to check the health status of the E2B API.

Get Sandbox

Tool to retrieve detailed information about a specific sandbox by its ID.

Get Sandbox Logs

Tool to retrieve logs from a specific E2B sandbox instance.

Get Sandbox Lifecycle Events

Tool to retrieve the latest lifecycle events for a particular sandbox instance.

Get Sandbox Metrics

Tool to retrieve timestamped CPU, memory, and disk usage metrics for a sandbox.

Get Team Metrics

Tool to retrieve timestamped CPU, memory, and disk usage metrics for a team.

Get Team Maximum Metrics

Tool to retrieve the maximum value for a specific team metric in a given interval.

Get Template Build Status

Tool to get the status of a template build.

Get Template Files

Tool to get an upload link for a tar file containing build layer files.

Get Webhook Configuration

Tool to retrieve the current webhook configuration for a specific webhook.

List All Sandboxes

Tool to list all running and paused sandboxes associated with your team.

List Sandboxes Metrics

Tool to retrieve timestamped CPU, memory, and disk usage metrics for multiple sandboxes.

List Team Sandbox Lifecycle Events

Tool to retrieve the latest lifecycle events across all sandboxes associated with the team.

List All Templates

Tool to list all available E2B templates for your team.

List All Webhooks

Tool to retrieve all registered webhooks for your team.

Pause Sandbox

Tool to pause a running E2B sandbox preserving its filesystem and memory state.

Create Sandbox

Tool to create a new E2B sandbox from a template.

Set Sandbox Timeout

Tool to set the timeout for an E2B sandbox.

Refresh Sandbox

Tool to refresh an E2B sandbox and extend its time to live.

Start Template Build

Tool to start a build for an E2B template.

Update Template

Tool to update an E2B template configuration.

Update Webhook Configuration

Tool to update an existing webhook configuration including URL, enabled status, and subscribed events.

FRAMEWORKS

How to build E2b MCP Agent with another framework

ChatGPT logo

ChatGPT

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OpenAI Agents SDK logo

OpenAI Agents SDK

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Claude Agent SDK logo

Claude Agent SDK

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Claude Code logo

Claude Code

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Claude Cowork logo

Claude Cowork

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Codex logo

Codex

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Cursor logo

Cursor

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OpenClaw logo

OpenClaw

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Hermes logo

Hermes

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CLI logo

CLI

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Google ADK logo

Google ADK

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LangChain logo

LangChain

Use E2b MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

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Mastra AI logo

Mastra AI

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LlamaIndex logo

LlamaIndex

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CrewAI logo

CrewAI

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OpenCode logo

OpenCode

Use E2b MCP with OpenCode

VS Code logo

VS Code

Use E2b MCP with VS Code

FAQ

Frequently asked questions

With a standalone E2b MCP server, the agents and LLMs can only access a fixed set of E2b tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from E2b and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. Pydantic AI fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right E2b tools.

Yes, absolutely. You can configure which E2b scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your E2b data and credentials are handled as safely as possible.

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A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

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