# How to integrate Baserow MCP with Autogen ```json { "title": "How to integrate Baserow MCP with Autogen", "toolkit": "Baserow", "toolkit_slug": "baserow", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/baserow/framework/autogen", "markdown_url": "https://composio.dev/toolkits/baserow/framework/autogen.md", "updated_at": "2026-05-12T10:02:31.548Z" } ``` ## 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 SDK](https://composio.dev/toolkits/baserow/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/baserow/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/baserow/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/baserow/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/baserow/framework/codex) - [OpenClaw](https://composio.dev/toolkits/baserow/framework/openclaw) - [Hermes](https://composio.dev/toolkits/baserow/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/baserow/framework/cli) - [Google ADK](https://composio.dev/toolkits/baserow/framework/google-adk) - [LangChain](https://composio.dev/toolkits/baserow/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/baserow/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/baserow/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/baserow/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/baserow/framework/crew-ai) ## 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. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `BASEROW_CREATE_USER` | Create User | Tool to create a new Baserow user with the provided details. Use when you need to register a new user account in Baserow. After creating an account, an initial workspace containing a database is automatically created. Optionally generates authentication JWT tokens if authenticate parameter is set to true. | | `BASEROW_DISPATCH_BUILDER_PAGE_DATA_SOURCE` | Dispatch Builder Page Data Source | Tool to dispatch the service of a builder page data source and return the result. Use when you need to execute a data source query in Baserow's builder application. | | `BASEROW_DISPATCH_PUBLIC_BUILDER_PAGE_DATA_SOURCE` | Dispatch Public Builder Page Data Source | Tool to dispatch the service of a published builder page data source and return the result. Use this when you need to execute a data source in a public/published Baserow builder domain. | | `BASEROW_GET_FORM_VIEW_METADATA` | Get Form View Metadata | Tool to retrieve metadata for a Baserow form view. Use when you need to get form structure and configuration details for constructing a form with the right fields. The form must be publicly shared or the user must have access to the related workspace. | | `BASEROW_GET_PUBLIC_BUILDER_BY_DOMAIN_NAME` | Get Public Builder by Domain Name | Tool to retrieve the public published version of a builder by its domain name. Use when you need to access a published Baserow builder application and its configuration, including pages, scripts, theme, and user sources. | | `BASEROW_GET_RECORD_NAMES_BUILDER_PAGE_DATA_SOURCE` | Get Record Names for Builder Page Data Source | Tool to find the record names associated with a given list of record ids. Use when you need to retrieve the display names for specific records from a builder page data source. | | `BASEROW_GET_SETTINGS` | Get Settings | Tool to retrieve all admin configured settings for the Baserow instance. Use when you need to check system-wide configuration like signup policies, email verification settings, or workspace creation permissions. | | `BASEROW_LIST_APPLICATION_USER_SOURCES` | List Application User Sources | Tool to list all user sources of an application if the user has access to the related application's workspace. Use when you need to retrieve user source configurations for a Baserow application. If the workspace is related to a template, this endpoint is publicly accessible. | | `BASEROW_LIST_AUTH_PROVIDERS_LOGIN_OPTIONS` | List Auth Providers Login Options | Tool to list available login options for configured authentication providers. Use when you need to discover which authentication methods are enabled for the Baserow instance. | | `BASEROW_LIST_DATABASES` | List Databases | This tool retrieves a list of all databases in a specified workspace. As a fundamental operation, it allows users to discover which databases are available in their Baserow workspace. This operation is independent and requires only authentication in order to fetch essential metadata for subsequent operations. | | `BASEROW_LIST_TABLES` | List Tables in Database | This tool lists all tables within a specified Baserow database. It allows users to retrieve information about all tables in a database by using the GET /api/database/{database_id}/tables/ endpoint. The expected output is an array of table objects containing details such as id, name, order, database_id, type, and first_row_header. | | `BASEROW_LIST_TEMPLATES` | List Templates | Tool to list all template categories and their related templates. The template's workspace_id can be used for previewing purposes because that workspace contains publicly accessible applications. Use when you need to discover available templates in Baserow. | | `BASEROW_SEND_PASSWORD_RESET_EMAIL` | Send Password Reset Email | Tool to send a password reset email to a user's email address. The email contains a password reset link that is valid for 48 hours. The endpoint will not fail if the email address is not found. | | `BASEROW_SEND_VERIFY_EMAIL` | Send Verification Email | Tool to send a verification email to a user's email address. Use when you need to trigger email verification for a user account that hasn't been verified yet. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Baserow MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Baserow. Instead of manually wiring Baserow APIs, OAuth, and scopes yourself, you get a structured, tool-based interface that an LLM can call safely. 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 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 ### 1. Getting API Keys for OpenAI and Composio OpenAI API Key - Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs). - Navigate to your API settings and generate a new API key. - Store this key securely as you'll need it for authentication. ### 2. Install dependencies 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 ```bash pip install composio python-dotenv pip install autogen-agentchat autogen-ext-openai autogen-ext-tools ``` ### 3. Set up environment variables 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 ```bash COMPOSIO_API_KEY=your-composio-api-key OPENAI_API_KEY=your-openai-api-key USER_ID=your-user-identifier@example.com ``` ### 4. Import dependencies and create Tool Router session 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 ```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 ``` ### 5. Configure MCP parameters for Autogen 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 ```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")} ) ``` ### 6. Create the model client and agent 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 ```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 ) ``` ### 7. Run the interactive chat loop 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 ```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") ``` ## Complete Code ```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. ## How to build Baserow MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/baserow/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/baserow/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/baserow/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/baserow/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/baserow/framework/codex) - [OpenClaw](https://composio.dev/toolkits/baserow/framework/openclaw) - [Hermes](https://composio.dev/toolkits/baserow/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/baserow/framework/cli) - [Google ADK](https://composio.dev/toolkits/baserow/framework/google-adk) - [LangChain](https://composio.dev/toolkits/baserow/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/baserow/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/baserow/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/baserow/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/baserow/framework/crew-ai) ## Related Toolkits - [Supabase](https://composio.dev/toolkits/supabase) - Supabase is an open-source backend platform offering scalable Postgres databases, authentication, storage, and real-time APIs. It lets developers build modern apps without managing infrastructure. - [Codeinterpreter](https://composio.dev/toolkits/codeinterpreter) - Codeinterpreter is a Python-based coding environment with built-in data analysis and visualization. It lets you instantly run scripts, plot results, and prototype solutions inside supported platforms. - [GitHub](https://composio.dev/toolkits/github) - GitHub is a code hosting platform for version control and collaborative software development. It streamlines project management, code review, and team workflows in one place. - [Ably](https://composio.dev/toolkits/ably) - Ably is a real-time messaging platform for live chat and data sync in modern apps. It offers global scale and rock-solid reliability for seamless, instant experiences. - [Abuselpdb](https://composio.dev/toolkits/abuselpdb) - Abuselpdb is a central database for reporting and checking IPs linked to malicious online activity. Use it to quickly identify and report suspicious or abusive IP addresses. - [Alchemy](https://composio.dev/toolkits/alchemy) - Alchemy is a blockchain development platform offering APIs and tools for Ethereum apps. It simplifies building and scaling Web3 projects with robust infrastructure. - [Algolia](https://composio.dev/toolkits/algolia) - Algolia is a hosted search API that powers lightning-fast, relevant search experiences for web and mobile apps. It helps developers deliver instant, typo-tolerant, and scalable search without complex infrastructure. - [Anchor browser](https://composio.dev/toolkits/anchor_browser) - Anchor browser is a developer platform for AI-powered web automation. It transforms complex browser actions into easy API endpoints for streamlined web interaction. - [Apiflash](https://composio.dev/toolkits/apiflash) - Apiflash is a website screenshot API for programmatically capturing web pages. It delivers high-quality screenshots on demand for automation, monitoring, or reporting. - [Apiverve](https://composio.dev/toolkits/apiverve) - Apiverve delivers a suite of powerful APIs that simplify integration for developers. It's designed for reliability and scalability so you can build faster, smarter applications without the integration headache. - [Appcircle](https://composio.dev/toolkits/appcircle) - Appcircle is an enterprise-grade mobile CI/CD platform for building, testing, and publishing mobile apps. It streamlines mobile DevOps so teams ship faster and with more confidence. - [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. - [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 Baserow MCP? 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. ### Can I use Tool Router MCP with Autogen? 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. ### Can I manage the permissions and scopes for Baserow while using Tool Router? 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. ### 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 Baserow data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) ยท [Composio docs](https://docs.composio.dev/llms.txt)