How to integrate Baserow MCP with Autogen

This guide walks you through connecting Baserow to AutoGen using the Composio tool router. By the end, you'll have a working Baserow agent that can list all databases in your main workspace, show tables in the marketing database, get details for tables in project database through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Baserow account through Composio's Baserow MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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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.

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Introduction

This guide walks you through connecting Baserow to AutoGen using the Composio tool router. By the end, you'll have a working Baserow agent that can list all databases in your main workspace, show tables in the marketing database, get details for tables in project database through natural language commands.

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

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

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

The Baserow MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Baserow account. It provides structured and secure access to your Baserow workspaces and databases, so your agent can perform actions like discovering databases, listing tables, and streamlining workspace exploration on your behalf.

  • Workspace database discovery: Have your agent quickly list all databases within any of your Baserow workspaces, making it easy to navigate large projects.
  • Table enumeration in databases: Let your agent fetch a full list of tables for any selected database, helping you understand and manage your data structures.
  • Metadata retrieval for planning: Enable your agent to gather essential metadata about databases and tables, laying the groundwork for more advanced automations or integrations.
  • Seamless data navigation: Guide your agent to explore and map your Baserow environment, so it can support you in building custom workflows or data pipelines.

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

Supported Tools

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

Create User

Tool to create a new Baserow user with the provided details.

Dispatch Builder Page Data Source

Tool to dispatch the service of a builder page data source and return the result.

Dispatch Public Builder Page Data Source

Tool to dispatch the service of a published builder page data source and return the result.

Get Form View Metadata

Tool to retrieve metadata for a Baserow form view.

Get Public Builder by Domain Name

Tool to retrieve the public published version of a builder by its domain name.

Get Record Names for Builder Page Data Source

Tool to find the record names associated with a given list of record ids.

Get Settings

Tool to retrieve all admin configured settings for the Baserow instance.

List Application User Sources

Tool to list all user sources of an application if the user has access to the related application's workspace.

List Auth Providers Login Options

Tool to list available login options for configured authentication providers.

List Databases

This tool retrieves a list of all databases in a specified workspace.

List Tables in Database

This tool lists all tables within a specified Baserow database.

List Templates

Tool to list all template categories and their related templates.

Send Password Reset Email

Tool to send a password reset email to a user's email address.

Send Verification Email

Tool to send a verification email to a user's email address.

FRAMEWORKS

How to build Baserow MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Baserow MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Baserow MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Baserow MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Baserow MCP with Claude Cowork

Codex logo

Codex

Use Baserow MCP with Codex

OpenClaw logo

OpenClaw

Use Baserow MCP with OpenClaw

Hermes logo

Hermes

Use Baserow MCP with Hermes

CLI logo

CLI

Use Baserow MCP with CLI

Google ADK logo

Google ADK

Use Baserow MCP with Google ADK

LangChain logo

LangChain

Use Baserow MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Baserow MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Baserow MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Baserow MCP with LlamaIndex

CrewAI logo

CrewAI

Use Baserow MCP with CrewAI

FAQ

Frequently asked questions

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

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

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