# How to integrate Baserow MCP with LangChain

```json
{
  "title": "How to integrate Baserow MCP with LangChain",
  "toolkit": "Baserow",
  "toolkit_slug": "baserow",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/baserow/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/baserow/framework/langchain.md",
  "updated_at": "2026-05-12T10:02:31.548Z"
}
```

## Introduction

This guide walks you through connecting Baserow to LangChain 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 LangChain 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)
- [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
- Connect your Baserow project to Composio
- Create a Tool Router MCP session for Baserow
- Initialize an MCP client and retrieve Baserow tools
- Build a LangChain agent that can interact with Baserow
- Set up an interactive chat interface for testing

## What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.
Key features include:
- Agent Framework: Build agents that can use tools and make decisions
- MCP Integration: Connect to external services through Model Context Protocol adapters
- Memory Management: Maintain conversation history across interactions
- Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

## 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 agent to Baserow. It provides structured and secure access so your agent can perform Baserow operations on your behalf through a secure, permission-based interface.
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

No description provided.

### 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

No description provided.
```python
pip install composio-langchain langchain-mcp-adapters langchain python-dotenv
```

```typescript
npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv
```

### 3. Set up environment variables

Create a .env file in your project root.
What's happening:
- COMPOSIO_API_KEY authenticates your requests to Composio's API
- COMPOSIO_USER_ID identifies the user for session management
- OPENAI_API_KEY enables access to OpenAI's language models
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import dependencies

No description provided.
```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
```

```typescript
import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();
```

### 5. Initialize Composio client

What's happening:
- We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
- Creating a Composio instance that will manage our connection to Baserow tools
- Validating that COMPOSIO_USER_ID is also set before proceeding
```python
async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
```

```typescript
const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });
```

### 6. Create a Tool Router session

What's happening:
- We're creating a Tool Router session that gives your agent access to Baserow tools
- The create method takes the user ID and specifies which toolkits should be available
- The returned session.mcp.url is the MCP server URL that your agent will use
- This approach allows the agent to dynamically load and use Baserow tools as needed
```python
# Create Tool Router session for Baserow
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['baserow']
)

url = session.mcp.url
```

```typescript
const session = await composio.create(
    userId as string,
    {
        toolkits: ['baserow']
    }
);

const url = session.mcp.url;
```

### 7. Configure the agent with the MCP URL

No description provided.
```python
client = MultiServerMCPClient({
    "baserow-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
```

```typescript
const client = new MultiServerMCPClient({
    "baserow-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });
```

### 8. Set up interactive chat interface

No description provided.
```python
conversation_history = []

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

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

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

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
```

```typescript
let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Baserow related question or task to the agent.\n");

const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
});

rl.prompt();

rl.on('line', async (userInput: string) => {
    const trimmedInput = userInput.trim();

    if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
        console.log("\nGoodbye!");
        rl.close();
        process.exit(0);
    }

    if (!trimmedInput) {
        rl.prompt();
        return;
    }

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });
```

### 9. Run the application

No description provided.
```python
if __name__ == "__main__":
    asyncio.run(main())
```

```typescript
main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
```

## Complete Code

```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['baserow']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "baserow-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Baserow related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

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

```typescript
import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['baserow']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "baserow-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Baserow related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    rl.prompt();

    rl.on('line', async (userInput: string) => {
        const trimmedInput = userInput.trim();
        
        if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
            console.log("\nGoodbye!");
            rl.close();
            process.exit(0);
        }
        
        if (!trimmedInput) {
            rl.prompt();
            return;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
```

## Conclusion

You've successfully built a LangChain agent that can interact with Baserow through Composio's Tool Router.
Key features of this implementation:
- Dynamic tool loading through Composio's Tool Router
- Conversation history maintenance for context-aware responses
- Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

## 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)
- [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)

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- [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.
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- [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 LangChain?

Yes, you can. LangChain 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) · [Composio docs](https://docs.composio.dev/llms.txt)