How to integrate Kaggle MCP with CrewAI

This guide walks you through connecting Kaggle to CrewAI using the Composio tool router. By the end, you'll have a working Kaggle agent that can download data files for the titanic competition, create a new version of your covid-19 dataset, check processing status of your uploaded dataset through natural language commands. This guide will help you understand how to give your CrewAI agent real control over a Kaggle account through Composio's Kaggle MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Kaggle

Api Key

Kaggle is a platform for data science and machine learning competitions, datasets, and collaborative notebooks. It makes it easy to find data, participate in challenges, and share insights with a global data community.

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Introduction

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

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

Also integrate Kaggle with

ChatGPT OpenAI Agents SDK Claude Agent SDK Claude Code Claude Cowork Codex OpenCode Cursor VS Code OpenClaw Hermes CLI Google ADK LangChain Vercel AI SDK Mastra AI LlamaIndex

TL;DR

Here's what you'll learn:

Get a Composio API key and configure your Kaggle connection
Set up CrewAI with an MCP enabled agent
Create a Tool Router session or standalone MCP server for Kaggle
Build a conversational loop where your agent can execute Kaggle operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

Agent Roles: Define specialized agents with specific goals and backstories
Task Management: Create tasks with clear descriptions and expected outputs
Crew Orchestration: Combine agents and tasks into collaborative workflows
MCP Integration: Connect to external tools through Model Context Protocol

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

The Kaggle MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Kaggle account. It provides structured and secure access to your Kaggle datasets, competitions, and configurations, so your agent can perform actions like downloading competition data, creating datasets, submitting entries, and managing dataset versions on your behalf.

Competition data access and download: Let your agent fetch and download competition datasets quickly by specifying a competition ID, so you always have the latest files for analysis.
Automated dataset creation and management: Have your agent create new Kaggle datasets, update metadata, and publish new dataset versions seamlessly, streamlining the process of sharing your work with the community.
Competition entry submission: Empower your agent to submit competition entries automatically once your solution is ready and uploaded, helping you participate in challenges without manual hassle.
Configuration management and setup: Allow your agent to initialize, locate, and update Kaggle API configuration files and keys, ensuring smooth and authenticated operations every time.
Dataset status monitoring: Ask your agent to check the status of uploaded datasets or processing jobs, so you always know when your data is ready for use or public sharing.

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:

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

Step-by-step Guide

Step by step08 STEPS

Prerequisites

Before starting, make sure you have:

Python 3.9 or higher
A Composio account and API key
A Kaggle connection authorized in Composio
An OpenAI API key for the CrewAI LLM
Basic familiarity with Python

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.

Install dependencies

bash

pip install composio crewai crewai-tools[mcp] python-dotenv

What's happening:

composio connects your agent to Kaggle via MCP
crewai provides Agent, Task, Crew, and LLM primitives
crewai-tools[mcp] includes MCP helpers
python-dotenv loads environment variables from .env

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_here

Create a .env file in your project root.

What's happening:

COMPOSIO_API_KEY authenticates with Composio
USER_ID scopes the session to your account
OPENAI_API_KEY lets CrewAI use your chosen OpenAI model

Import dependencies

python

import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

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

if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")

What's happening:

CrewAI classes define agents and tasks, and run the workflow
MCPServerHTTP connects the agent to an MCP endpoint
Composio will give you a short lived Kaggle MCP URL

Create a Composio Tool Router session for Kaggle

python

composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["kaggle"])

url = session.mcp.url

What's happening:

You create a Kaggle only session through Composio
Composio returns an MCP HTTP URL that exposes Kaggle tools

Initialize the MCP Server

python

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )

What's Happening:

Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.

Create a CLI Chatloop and define the Crew

python

print("Chat started! Type 'exit' or 'quit' to end.\n")

conversation_context = ""

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")

What's Happening:

Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.

Complete Code

Here's the complete code to get you started with Kaggle and CrewAI:

python

from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

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.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["kaggle"],
)
url = session.mcp.url

# Configure LLM
llm = LLM(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY"),
)

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\n")

    conversation_context = ""

    while True:
        user_input = input("You: ").strip()

        if user_input.lower() in ["exit", "quit", "bye"]:
            print("\nGoodbye!")
            break

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

Conclusion

You now have a CrewAI agent connected to Kaggle through Composio's Tool Router. The agent can perform Kaggle operations through natural language commands.

Next steps:

Add role-specific instructions to customize agent behavior
Plug in more toolkits for multi-app workflows
Chain tasks for complex multi-step operations

TOOLS

Supported Tools

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

Download competition data files

Downloads all data files for a Kaggle competition as a single zip archive.

Submit Competition Entry

Submit an entry to a Kaggle competition using a previously uploaded file.

Get Kaggle Config Directory

Tool to retrieve the directory of the Kaggle API configuration file.

Initialize Kaggle Configuration

Initialize Kaggle API client configuration.

List Kaggle Configuration Keys

Tool to list local Kaggle API configuration keys.

Get Kaggle Config Path

Tool to retrieve local Kaggle API configuration file path.

Reset Kaggle Configuration

Tool to reset local Kaggle CLI configuration to defaults.

Set Kaggle Configuration

Tool to set a Kaggle CLI configuration parameter.

Unset Kaggle Configuration

Tool to unset a Kaggle CLI configuration parameter.

View Kaggle Configuration

View local Kaggle API credentials and configuration settings.

Dataset Create

Create a new Kaggle dataset with metadata.

Kaggle Dataset Init

Tool to initialize a dataset-metadata.

List Kaggle Dataset Files

Tool to list files in a Kaggle dataset.

Get Dataset Status

Check the processing status of a Kaggle dataset after creation or version update.

Create Dataset Version

Create a new version of an existing Kaggle dataset.

Download competition file

Tool to download a specific data file from a Kaggle competition.

Download competition leaderboard

Tool to download the entire competition leaderboard as a CSV file packaged in a ZIP archive.

Download Kaggle Dataset

Tool to download all files from a Kaggle dataset as a zip archive.

Download Kaggle Dataset File

Tool to download a specific file from a Kaggle dataset.

Generate Competition Submission URL

Tool to generate a pre-signed URL for uploading competition submission files.

Get Dataset Metadata

Tool to get comprehensive metadata for a Kaggle dataset including title, description, licenses, and tags.

Get Model Details

Tool to get a Kaggle model's details including metadata and description.

Get Model Instance Details

Tool to get details for a specific Kaggle model instance (variation).

Kaggle Kernel Init

Initialize a kernel-metadata.

Download kernel output

Tool to download the output of a Kaggle kernel.

Get Kernel Status

Get the execution status of a Kaggle kernel (notebook).

List competition data files

Tool to list all data files available for a Kaggle competition.

List Kaggle Competitions

Tool to list available Kaggle competitions with filters and pagination.

List Kaggle Datasets

Tool to list Kaggle datasets with filters and pagination.

List Kernel Output Files

Tool to list output files for a specific kernel run.

List Kaggle Kernels

Tool to list Kaggle kernels (notebooks and scripts) with filters and pagination.

List Model Instance Version Files

Tool to list files for a specific version of a model variation.

List Kaggle Models

Tool to list Kaggle models with optional filters for owner, sorting, search, and pagination.

Pull Kernel Code

Tool to pull (download) the source code of a Kaggle kernel to local storage.

View competition leaderboard

Tool to view competition leaderboard information showing rankings and scores of participants.

FRAMEWORKS

How to build Kaggle MCP Agent with another framework

ChatGPT

Use Kaggle MCP with ChatGPT

OpenAI Agents SDK

Use Kaggle MCP with OpenAI Agents SDK

Claude Agent SDK

Use Kaggle MCP with Claude Agent SDK

Claude Code

Use Kaggle MCP with Claude Code

Claude Cowork

Use Kaggle MCP with Claude Cowork

Codex

Use Kaggle MCP with Codex

Cursor

Use Kaggle MCP with Cursor

OpenClaw

Use Kaggle MCP with OpenClaw

Hermes

Use Kaggle MCP with Hermes

CLI

Use Kaggle MCP with CLI

Google ADK

Use Kaggle MCP with Google ADK

LangChain

Use Kaggle MCP with LangChain

Vercel AI SDK

Use Kaggle MCP with Vercel AI SDK

Mastra AI

Use Kaggle MCP with Mastra AI

LlamaIndex

Use Kaggle MCP with LlamaIndex

OpenCode

Use Kaggle MCP with OpenCode

VS Code

Use Kaggle MCP with VS Code

MORE TOOLKITS

Explore Other Toolkits

Toolkit marketplace

Composio

No Auth

Composio is an integration platform that connects AI agents with hundreds of business tools. It streamlines authentication and lets you trigger actions across services—no custom code needed.

Composio search

No Auth

Composio search is a unified web search toolkit spanning travel, e-commerce, news, financial markets, images, and more. It lets you and your apps tap into up-to-date web data from a single, easy-to-integrate service.

Perplexityai

Api Key

Perplexityai delivers natural, conversational AI models for generating human-like text. Instantly get context-aware, high-quality responses for chat, search, or complex workflows.

Browser tool

No Auth

Browser tool is a virtual browser integration that lets AI agents interact with the web programmatically. It enables automated browsing, scraping, and action-taking from any AI workflow.

FAQ

Frequently asked questions

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

Yes, you can. CrewAI 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 Kaggle tools.

Yes, absolutely. You can configure which Kaggle 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 Kaggle data and credentials are handled as safely as possible.

Start with Kaggle.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Kaggle tool your agent needs.Free to start.

Start building

Customer stories

Teams ship real agents on Composio

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Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati

Co-founder, Slashy

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.

Abhi Arya

Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave

CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu

Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola

Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Jerome Leclanche

Co-Founder, Ingram Technologies

How to integrate Kaggle MCP with CrewAI

Connect Kaggle without auth hassles

Introduction

Also integrate Kaggle with

TL;DR

What is CrewAI?

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

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

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI and Composio

Install dependencies

Set up environment variables

Import dependencies

Create a Composio Tool Router session for Kaggle

Initialize the MCP Server

Create a CLI Chatloop and define the Crew

Complete Code

Conclusion

Supported Tools

How to build Kaggle MCP Agent with another framework

ChatGPT

OpenAI Agents SDK

Claude Agent SDK

Claude Code

Claude Cowork

Codex

Cursor

OpenClaw

Hermes

CLI

Google ADK

LangChain

Vercel AI SDK

Mastra AI

LlamaIndex

OpenCode

VS Code

Explore Other Toolkits

Composio

Composio search

Perplexityai

Browser tool

Frequently asked questions

What are the differences in Tool Router MCP and Kaggle MCP?+

Can I use Tool Router MCP with CrewAI?+

Can I manage the permissions and scopes for Kaggle while using Tool Router?+

How safe is my data with Composio Tool Router?+

Start with Kaggle.It takes 30 seconds.

Teams ship real agents on Composio