How to integrate 0CodeKit MCP with Autogen

This guide walks you through connecting 0CodeKit to AutoGen using the Composio tool router. By the end, you'll have a working 0CodeKit agent that can convert json data into csv file, generate qr code for checkout link, extract text from uploaded pdf through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a 0CodeKit account through Composio's 0CodeKit MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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0CodeKit is a utility API platform for AI, document, image, and data workflows. Use it to convert, validate, generate, store, and automate data without custom backend code.

8 Tools

Introduction

This guide walks you through connecting 0CodeKit to AutoGen using the Composio tool router. By the end, you'll have a working 0CodeKit agent that can convert json data into csv file, generate qr code for checkout link, extract text from uploaded pdf through natural language commands.

This guide will help you understand how to give your AutoGen agent real control over a 0CodeKit account through Composio's 0CodeKit MCP server.

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

Also integrate 0CodeKit with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for 0CodeKit
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call 0CodeKit tools
  • Run a live chat loop where you ask the agent to perform 0CodeKit operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

  • Multi-Agent Systems: Build collaborative agent workflows
  • MCP Workbench: Native support for Model Context Protocol tools
  • Streaming HTTP: Connect to external services through streamable HTTP
  • AssistantAgent: Pre-built agent class for tool-using assistants

What is the 0CodeKit MCP server, and what's possible with it?

The 0CodeKit MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your 0CodeKit account. It provides structured and secure access to text, validation, conversion, date, and calculation utilities, so your agent can validate emails, find keywords, parse campaign links, hash messages, and calculate BMI on your behalf.

  • Email validation: Have your agent check whether an email address is valid and retrieve the corrected address when available.
  • Text search and hashing: Let the agent locate keywords and their positions in text, or generate a cryptographic digest or HMAC for a message.
  • Campaign link analysis: Direct your agent to extract standard UTM campaign details from a URL.
  • Country and date checks: Instruct your agent to convert country names and ISO codes, or determine whether a date falls on a weekend.
  • Health estimates and credit checks: Have your agent calculate BMI with related weight, energy, and nutrient estimates, or check your remaining 0CodeKit credits.

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 step08 STEPS
1

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A 0CodeKit account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
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 python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to 0CodeKit via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

  • COMPOSIO_API_KEY is required to talk to Composio
  • OPENAI_API_KEY is used by Autogen's OpenAI client
  • USER_ID is how Composio identifies which user's 0CodeKit connections to use
5

Import dependencies and create Tool Router session

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a 0CodeKit session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["0codekit"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes 0CodeKit tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

Configure MCP parameters for Autogen

python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

  • url points to the Tool Router MCP endpoint from Composio
  • timeout is the HTTP timeout for requests
  • sse_read_timeout controls how long to wait when streaming responses
  • terminate_on_close=True cleans up the MCP server process when the workbench is closed
7

Create the model client and agent

python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create 0CodeKit assistant agent with MCP tools
    agent = AssistantAgent(
        name="0codekit_assistant",
        description="An AI assistant that helps with 0CodeKit operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the 0CodeKit tools from the workbench
8

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any 0CodeKit related question or task to the agent.\n")

# Conversation loop
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")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which 0CodeKit tools to call via MCP
  • agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
  • Typing exit, quit, or bye ends the loop

Complete Code

Here's the complete code to get you started with 0CodeKit and AutoGen:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a 0CodeKit session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["0codekit"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create 0CodeKit assistant agent with MCP tools
        agent = AssistantAgent(
            name="0codekit_assistant",
            description="An AI assistant that helps with 0CodeKit operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any 0CodeKit related question or task to the agent.\n")

        # Conversation loop
        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")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

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

Conclusion

You now have an Autogen assistant wired into 0CodeKit through Composio's Tool Router and MCP. From here you can:
  • Add more toolkits to the toolkits list, for example notion or hubspot
  • Refine the agent description to point it at specific workflows
  • Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for 0CodeKit, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

Every 0CodeKit action and event your agent gets out of the box.

Calculate BMI

Calculate body mass index and the provider's related desirable-weight, daily-energy, and nutrient estimates from weight in kilograms and height in centimeters.

Check Weekend

Determine whether a date is a weekend and return its weekday name and day number.

Convert Nation and ISO Code

Convert either an English country name to its ISO code or an ISO code to its English country name.

Find Keywords

Search text for one or more keywords and report whether each occurs and the zero-based positions of matches.

Get Remaining Credits

Return the number of 0CodeKit credits remaining for the connected API key.

Hash Message

Generate a cryptographic digest or HMAC for a text message using a supported algorithm.

Parse UTM Parameters

Extract standard UTM campaign parameters from a URL.

Validate Email

Check an email address using 0CodeKit and return whether it is valid plus the provider's corrected-address value.

FRAMEWORKS

How to build 0CodeKit MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use 0CodeKit MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use 0CodeKit MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use 0CodeKit MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use 0CodeKit MCP with Claude Cowork

Codex logo

Codex

Use 0CodeKit MCP with Codex

OpenClaw logo

OpenClaw

Use 0CodeKit MCP with OpenClaw

Hermes logo

Hermes

Use 0CodeKit MCP with Hermes

CLI logo

CLI

Use 0CodeKit MCP with CLI

Google ADK logo

Google ADK

Use 0CodeKit MCP with Google ADK

LangChain logo

LangChain

Use 0CodeKit MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use 0CodeKit MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use 0CodeKit MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use 0CodeKit MCP with LlamaIndex

CrewAI logo

CrewAI

Use 0CodeKit MCP with CrewAI

FAQ

Frequently asked questions

With a standalone 0CodeKit MCP server, the agents and LLMs can only access a fixed set of 0CodeKit tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from 0CodeKit and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. Autogen 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 0CodeKit tools.

Yes, absolutely. You can configure which 0CodeKit 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 0CodeKit data and credentials are handled as safely as possible.

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