# How to integrate Codeinterpreter MCP with Google ADK

```json
{
  "title": "How to integrate Codeinterpreter MCP with Google ADK",
  "toolkit": "Codeinterpreter",
  "toolkit_slug": "codeinterpreter",
  "framework": "Google ADK",
  "framework_slug": "google-adk",
  "url": "https://composio.dev/toolkits/codeinterpreter/framework/google-adk",
  "markdown_url": "https://composio.dev/toolkits/codeinterpreter/framework/google-adk.md",
  "updated_at": "2026-05-06T08:06:43.629Z"
}
```

## Introduction

This guide walks you through connecting Codeinterpreter to Google ADK using the Composio tool router. By the end, you'll have a working Codeinterpreter agent that can run this python script and show output, generate a line chart from your csv file, upload a dataset and summarize key stats through natural language commands.
This guide will help you understand how to give your Google ADK agent real control over a Codeinterpreter account through Composio's Codeinterpreter MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Codeinterpreter with

- [OpenAI Agents SDK](https://composio.dev/toolkits/codeinterpreter/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/codeinterpreter/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/codeinterpreter/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/codeinterpreter/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/codeinterpreter/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/codeinterpreter/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/codeinterpreter/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/codeinterpreter/framework/cli)
- [LangChain](https://composio.dev/toolkits/codeinterpreter/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/codeinterpreter/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/codeinterpreter/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/codeinterpreter/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/codeinterpreter/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Get a Codeinterpreter account set up and connected to Composio
- Install the Google ADK and Composio packages
- Create a Composio Tool Router session for Codeinterpreter
- Build an agent that connects to Codeinterpreter through MCP
- Interact with Codeinterpreter using natural language

## What is Google ADK?

Google ADK (Agents Development Kit) is Google's framework for building AI agents powered by Gemini models. It provides tools for creating agents that can use external services through the Model Context Protocol.
Key features include:
- Gemini Integration: Native support for Google's Gemini models
- MCP Toolset: Built-in support for Model Context Protocol tools
- Streamable HTTP: Connect to external services through streamable HTTP
- CLI and Web UI: Run agents via command line or web interface

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

The Codeinterpreter MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Codeinterpreter environment. It provides structured and secure access to interactive Python sandboxes, so your agent can run scripts, analyze data, visualize results, and manage files on your behalf.
- On-demand code execution: Instantly execute Python code snippets, scripts, or notebooks and receive real-time output, including errors and logs.
- Sandbox creation and management: Have your agent spin up isolated coding environments for running experiments, testing ideas, or working with data securely.
- File upload and retrieval: Seamlessly upload datasets, scripts, or assets to the sandbox and fetch generated files, reports, or images for further analysis.
- Terminal command automation: Direct your agent to run Linux shell commands inside the sandbox, enabling advanced automation and environment setup.
- Data visualization and reporting: Generate charts, plots, and visual reports by executing code that saves outputs as files—perfect for data-driven tasks.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `CODEINTERPRETER_CREATE_SANDBOX` | Create Sandbox | Create a sandbox to execute python code in a jupyter notebook cell. this is useful for agents to communicate, execute code, see output, read files, write files, etc. it's like you own personal computer, but in the cloud. use /home/user folder to write/read files. |
| `CODEINTERPRETER_EXECUTE_CODE` | Execute Code | Execute python code in a sandbox and return any result, stdout, stderr, and error. use /home/user folder to write/read files. try to not use plt.show() as the code is executed remotely. use files for image/chart output instead. |
| `CODEINTERPRETER_GET_FILE_CMD` | Get File | Get a file from the sandbox and returns the file. the files should be read from /home/user folder. |
| `CODEINTERPRETER_RUN_TERMINAL_CMD` | Run Terminal Command | Run a command in the terminal and returns the stdout, stderr, and error code. use /home/user folder to write/read files. |
| `CODEINTERPRETER_UPLOAD_FILE_CMD` | Upload File | Upload a file to the sandbox environment. the files should be uploaded to the /home/user folder. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Codeinterpreter MCP server is an implementation of the Model Context Protocol that connects your AI agent to Codeinterpreter. It provides structured and secure access so your agent can perform Codeinterpreter operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

Before starting, make sure you have:
- A Google API key for Gemini models
- A Composio account and API key
- Python 3.9 or later installed
- Basic familiarity with Python

### 1. Getting API Keys for Google and Composio

Google API Key
- Go to [Google AI Studio](https://aistudio.google.com/app/apikey) and create an API key.
- Copy the key and keep it safe. You will put this in GOOGLE_API_KEY.
Composio API Key and User ID
- Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Go to Settings → API Keys and copy your Composio API key. Use this for COMPOSIO_API_KEY.
- Decide on a stable user identifier to scope sessions, often your email or a user ID. Use this for COMPOSIO_USER_ID.

### 2. Install dependencies

Inside your virtual environment, install the required packages.
What's happening:
- google-adk is Google's Agents Development Kit
- composio connects your agent to Codeinterpreter via MCP
- python-dotenv loads environment variables
```bash
pip install google-adk composio python-dotenv
```

### 3. Set up ADK project

Set up a new Google ADK project.
What's happening:
- This creates an agent folder with a root agent file and .env file
```bash
adk create my_agent
```

### 4. Set environment variables

Save all your credentials in the .env file.
What's happening:
- GOOGLE_API_KEY authenticates with Google's Gemini models
- COMPOSIO_API_KEY authenticates with Composio
- COMPOSIO_USER_ID identifies the user for session management
```bash
GOOGLE_API_KEY=your-google-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id-or-email
```

### 5. Import modules and validate environment

What's happening:
- os reads environment variables
- Composio is the main Composio SDK client
- GoogleProvider declares that you are using Google ADK as the agent runtime
- Agent is the Google ADK LLM agent class
- McpToolset lets the ADK agent call MCP tools over HTTP
```python
import os
import warnings

from composio import Composio
from dotenv import load_dotenv
from google.adk.agents.llm_agent import Agent
from google.adk.tools.mcp_tool.mcp_session_manager import StreamableHTTPConnectionParams
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset

load_dotenv()

warnings.filterwarnings("ignore", message=".*BaseAuthenticatedTool.*")

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")
```

### 6. Create Composio client and Tool Router session

What's happening:
- Authenticates to Composio with your API key
- Declares Google ADK as the provider
- Spins up a short-lived MCP endpoint for your user and selected toolkit
- Stores the MCP HTTP URL for the ADK MCP integration
```python
composio_client = Composio(api_key=COMPOSIO_API_KEY)

composio_session = composio_client.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["codeinterpreter"],
)

COMPOSIO_MCP_URL = composio_session.mcp.url,
print(f"Composio MCP URL: {COMPOSIO_MCP_URL}")
```

### 7. Set up the McpToolset and create the Agent

What's happening:
- Connects the ADK agent to the Composio MCP endpoint through McpToolset
- Uses Gemini as the model powering the agent
- Lists exact tool names in instruction to reduce misnamed tool calls
```python
composio_toolset = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url=COMPOSIO_MCP_URL,
        headers={"x-api-key": COMPOSIO_API_KEY}
    )
)

root_agent = Agent(
    model="gemini-2.5-flash",
    name="composio_agent",
    description="An agent that uses Composio tools to perform actions.",
    instruction=(
        "You are a helpful assistant connected to Composio. "
        "You have the following tools available: "
        "COMPOSIO_SEARCH_TOOLS, COMPOSIO_MULTI_EXECUTE_TOOL, "
        "COMPOSIO_MANAGE_CONNECTIONS, COMPOSIO_REMOTE_BASH_TOOL, COMPOSIO_REMOTE_WORKBENCH. "
        "Use these tools to help users with Codeinterpreter operations."
    ),
    tools=[composio_toolset],
)

print("\nAgent setup complete. You can now run this agent directly ;)")
```

### 8. Run the agent

Execute the agent from the project root. The web command opens a web portal where you can chat with the agent.
What's happening:
- adk run runs the agent in CLI mode
- adk web . opens a web UI for interactive testing
```bash
# Run in CLI mode
adk run my_agent

# Or run in web UI mode
adk web
```

## Complete Code

```python
import os
import warnings

from composio import Composio
from composio_google import GoogleProvider
from dotenv import load_dotenv
from google.adk.agents.llm_agent import Agent
from google.adk.tools.mcp_tool.mcp_session_manager import StreamableHTTPConnectionParams
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset

load_dotenv()
warnings.filterwarnings("ignore", message=".*BaseAuthenticatedTool.*")

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

composio_client = Composio(api_key=COMPOSIO_API_KEY, provider=GoogleProvider())

composio_session = composio_client.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["codeinterpreter"],
)

COMPOSIO_MCP_URL = composio_session.mcp.url


composio_toolset = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url=COMPOSIO_MCP_URL,
        headers={"x-api-key": COMPOSIO_API_KEY}
    )
)

root_agent = Agent(
    model="gemini-2.5-flash",
    name="composio_agent",
    description="An agent that uses Composio tools to perform actions.",
    instruction=(
        "You are a helpful assistant connected to Composio. "
        "You have the following tools available: "
        "COMPOSIO_SEARCH_TOOLS, COMPOSIO_MULTI_EXECUTE_TOOL, "
        "COMPOSIO_MANAGE_CONNECTIONS, COMPOSIO_REMOTE_BASH_TOOL, COMPOSIO_REMOTE_WORKBENCH. "
        "Use these tools to help users with Codeinterpreter operations."
    ),  
    tools=[composio_toolset],
)

print("\nAgent setup complete. You can now run this agent directly ;)")
```

## Conclusion

You've successfully integrated Codeinterpreter with the Google ADK through Composio's MCP Tool Router. Your agent can now interact with Codeinterpreter using natural language commands.
Key takeaways:
- The Tool Router approach dynamically routes requests to the appropriate Codeinterpreter tools
- Environment variables keep your credentials secure and separate from code
- Clear agent instructions reduce tool calling errors
- The ADK web UI provides an interactive interface for testing and development
You can extend this setup by adding more toolkits to the toolkits array in your session configuration.

## How to build Codeinterpreter MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/codeinterpreter/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/codeinterpreter/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/codeinterpreter/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/codeinterpreter/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/codeinterpreter/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/codeinterpreter/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/codeinterpreter/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/codeinterpreter/framework/cli)
- [LangChain](https://composio.dev/toolkits/codeinterpreter/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/codeinterpreter/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/codeinterpreter/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/codeinterpreter/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/codeinterpreter/framework/crew-ai)

## Related Toolkits

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- [Appdrag](https://composio.dev/toolkits/appdrag) - Appdrag is a cloud platform for building websites, APIs, and databases with drag-and-drop tools and code editing. It accelerates development and iteration by combining hosting, database management, and low-code features in one place.
- [Appveyor](https://composio.dev/toolkits/appveyor) - AppVeyor is a cloud-based continuous integration service for building, testing, and deploying applications. It helps developers automate and streamline their software delivery pipelines.
- [Backendless](https://composio.dev/toolkits/backendless) - Backendless is a backend-as-a-service platform for mobile and web apps, offering database, file storage, user authentication, and APIs. It helps developers ship scalable applications faster without managing server infrastructure.
- [Baserow](https://composio.dev/toolkits/baserow) - Baserow is an open-source no-code database platform for building collaborative data apps. It makes it easy for teams to organize data and automate workflows without writing code.
- [Bench](https://composio.dev/toolkits/bench) - Bench is a benchmarking tool for automated performance measurement and analysis. It helps you quickly evaluate, compare, and track your systems or workflows.
- [Better stack](https://composio.dev/toolkits/better_stack) - Better Stack is a monitoring, logging, and incident management solution for apps and services. It helps teams ensure application reliability and performance with real-time insights.
- [Bitbucket](https://composio.dev/toolkits/bitbucket) - Bitbucket is a Git-based code hosting and collaboration platform for teams. It enables secure repository management and streamlined code reviews.
- [Blazemeter](https://composio.dev/toolkits/blazemeter) - Blazemeter is a continuous testing platform for web and mobile app performance. It empowers teams to automate and analyze large-scale tests with ease.
- [Blocknative](https://composio.dev/toolkits/blocknative) - Blocknative delivers real-time mempool monitoring and transaction management for public blockchains. Instantly track pending transactions and optimize blockchain interactions with live data.
- [Bolt iot](https://composio.dev/toolkits/bolt_iot) - Bolt IoT is a platform for building and managing IoT projects with cloud-based device control and monitoring. It makes connecting sensors and actuators to the internet seamless for automation and data insights.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Codeinterpreter MCP?

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

### Can I use Tool Router MCP with Google ADK?

Yes, you can. Google ADK 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 Codeinterpreter tools.

### Can I manage the permissions and scopes for Codeinterpreter while using Tool Router?

Yes, absolutely. You can configure which Codeinterpreter 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.

### How safe is my data with Composio Tool Router?

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 Codeinterpreter data and credentials are handled as safely as possible.

---
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