How to integrate Basin MCP with Autogen

This guide walks you through connecting Basin to AutoGen using the Composio tool router. By the end, you'll have a working Basin agent that can create a new form for event signups, delete an old feedback form from project, get details of your contact form through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Basin account through Composio's Basin MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Api Key

Basin is a no-code form backend for quickly setting up reliable contact forms. It lets you collect and manage form submissions without writing any server-side code.

19 Tools

Introduction

This guide walks you through connecting Basin to AutoGen using the Composio tool router. By the end, you'll have a working Basin agent that can create a new form for event signups, delete an old feedback form from project, get details of your contact form through natural language commands.

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

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

Also integrate Basin 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 Basin
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Basin tools
  • Run a live chat loop where you ask the agent to perform Basin 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 Basin MCP server, and what's possible with it?

The Basin MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Basin account. It provides structured and secure access to your forms and projects, so your agent can perform actions like creating forms, managing webhooks, organizing projects, and retrieving domain or form details on your behalf.

  • Instant form creation and management: Ask your agent to set up new forms with custom settings, associate them with projects, or delete forms you no longer need—all without manual coding.
  • Seamless project organization: Let your agent create new Basin projects to group related forms or delete obsolete projects, keeping your workspace tidy and efficient.
  • Automated webhook and integration setup: Have your agent add or remove webhooks for specific forms, so submissions are instantly routed to the right endpoints or external services.
  • Detailed form and account insights: Retrieve rich metadata about any form or get a full list of domains linked to your Basin account, helping you monitor and audit your form infrastructure.
  • Effortless notification management: Empower your agent to configure notification webhooks, ensuring critical submissions reach your team or external tools in real time.

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 Basin 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 Basin 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 Basin 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 Basin session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["basin"]
    )
    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 Basin 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 Basin assistant agent with MCP tools
    agent = AssistantAgent(
        name="basin_assistant",
        description="An AI assistant that helps with Basin 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 Basin 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 Basin 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 Basin 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 Basin 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 Basin session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["basin"]
    )
    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 Basin assistant agent with MCP tools
        agent = AssistantAgent(
            name="basin_assistant",
            description="An AI assistant that helps with Basin 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 Basin 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 Basin 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 Basin, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

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

Create Form

Tool to create a new form in Basin.

Create Form Webhook

Tool to create a new webhook for a specific form.

Create Project

Tool to create a new Basin project.

Delete Form

Tool to delete a form.

Delete Project

Tool to delete a project.

Delete Submission

Tool to permanently delete a form submission by its ID.

Delete Webhook

Tool to delete a specific webhook.

Get Domains

Tool to retrieve a list of all custom domains associated with the Basin account.

Get Form Details

Retrieves comprehensive details about a specific Basin form including configuration, notification settings, security options, branding, webhooks, and submission counts.

Get Forms

Retrieves a list of all Basin forms with their configuration and metadata.

Get Form Webhook

Tool to retrieve details of a specific form webhook by its ID.

Get Project Details

Tool to retrieve detailed information about a specific project.

Get Projects

Retrieves a list of Basin projects from your account.

Get Submissions

Retrieve form submissions from Basin with optional filtering, sorting, and search capabilities.

Get Webhooks

Tool to retrieve all webhooks associated with a specific form.

List Form Views

Retrieves a list of all Basin form views with their configuration and metadata.

Update Form

Tool to update an existing Basin form by ID.

Update Project

Tool to update details of an existing project.

Update Webhook

Tool to update settings of an existing webhook for a form.

FRAMEWORKS

How to build Basin MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Basin MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Basin MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Basin MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Basin MCP with Claude Cowork

Codex logo

Codex

Use Basin MCP with Codex

OpenClaw logo

OpenClaw

Use Basin MCP with OpenClaw

Hermes logo

Hermes

Use Basin MCP with Hermes

CLI logo

CLI

Use Basin MCP with CLI

Google ADK logo

Google ADK

Use Basin MCP with Google ADK

LangChain logo

LangChain

Use Basin MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Basin MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Basin MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Basin MCP with LlamaIndex

CrewAI logo

CrewAI

Use Basin MCP with CrewAI

FAQ

Frequently asked questions

With a standalone Basin MCP server, the agents and LLMs can only access a fixed set of Basin tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Basin 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 Basin tools.

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

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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.

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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.

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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.

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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.

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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.

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Co-Founder, Ingram Technologies