Baserow MCP for AI Agents. Manage Structured Data with Conversation.

Q: How do I check which databases Baserow MCP can access?

You use the listworkspaces tool. This command provides an overview of every high-level workspace connected to your account, letting you know what systems are available for management.

Q: Can I read data from multiple tables at once using Baserow MCP?

Yes, by combining tools. You first use listtables to identify all relevant sources, and then ask your agent to run listrows against each table you need.

Q: What if I don't know the ID of a row I want to update?

You can use listrows first. By providing search criteria (like 'Project Name: Alpha'), the agent will find the matching records and give you the necessary IDs before you run updaterow.

Q: Does Baserow MCP support large data sets?

Yes, the tools are designed for scale. The listrows tool specifically supports pagination and search, meaning it can handle listing many records without timing out.

Baserow MCP connects your AI agent directly to your no-code relational database. Manage, query, and update structured data without ever opening a web browser or writing SQL. You tell your AI client what you need—whether it's listing all project applications or updating a user status—and it handles the complex data operations instantly.

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

See Vinkius in Action

Give Claude and any AI agent real-world access

Manage Database Structure

List and monitor all workspaces, applications, fields, and tables within your Baserow setup.

Perform Data Reads (Querying)

Retrieve specific record details or list paginated rows from any table using natural language search criteria.

Update and Modify Records

Programmatically create new records in a row or modify existing data fields with simple instructions.

Maintain Data Integrity

Delete specific rows when they are no longer needed, ensuring your data ledger stays clean and accurate.

Ask an AI about this

Waiting for input…

AI Agent

What AI agents can do with Baserow MCP: 9 Data Management Tools

These tools allow your agent to perform every necessary action on your no-code backend, from listing all applications to updating individual records.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using Baserow MCP

List Applications

Shows all distinct Baserow applications (databases) you have set up.

Create Row

Creates a brand new record in any specified table, requiring field names and values...

Delete Row

Permanently removes a specific row from a given table.

List Fields

Retrieves the names and types of all fields available within a chosen table.

Get Row

Fetches detailed data for one specific row, using its unique identifier.

List Rows

Searches and lists multiple rows in a table; supports pagination and search terms.

List Tables

Displays all available tables within a selected database application.

Update Row

Modifies the data in an existing row, requiring both the row's identifier and new...

List Workspaces

Lists every workspace connected to your Baserow account.

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Claude AI

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

Start a conversation

Open a new chat. The Baserow integration is available immediately — no restart needed.

Antigravity

Configure Agent Environment

Open your Antigravity agent's workspace configuration or mcp-servers.json file.

Bind the Endpoint

Add the Vinkius endpoint URL to your agent's MCP connections list:

"mcp_servers": {
  "baserow-alternative": {
    "serverUrl": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
  }
}

Provide your secure token in place of [YOUR_TOKEN_HERE] to ensure your agent requests are authenticated.

Execute

Start your Antigravity session. The agent will autonomously discover and utilize the Baserow tools with full Vinkius guardrails applied.

VS Code Copilot

⚡

One-Click Install (Recommended)

In your Vinkius Dashboard, simply click the Add to VS Code button for this server. We'll automatically configure your local workspace.

Or configure manually

Open MCP Settings

Open VS Code, press Ctrl/Cmd + Shift + P, and search for GitHub Copilot: MCP Servers.

Add Server Config

Add the Vinkius endpoint configuration to your mcp-servers.json file:

"baserow-alternative": {
  "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}

Ensure you replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.

LangChain

Install Dependencies

Install the LangChain MCP adapters for your environment:

pip install langchain-mcp-adapters

Connect the Server

Use the SSEClient in LangChain to connect to the Vinkius managed endpoint:

from langchain_mcp_adapters.client import SSEClient

# Connect to Vinkius
client = SSEClient(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
tools = client.get_tools()

CrewAI

Define the Tool

Load the Vinkius MCP tools into your CrewAI agents:

from crewai import Agent
from mcp_crewai import MCPTool

# Connect securely to Vinkius
vinkius_tools = MCPTool(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

# Assign to Agent
researcher = Agent(
    role='Data Researcher',
    tools=vinkius_tools.get_all()
)

Execute Task

Run your CrewAI process. The agent will autonomously route tasks to the Vinkius managed server.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

Import from OpenAPI, Swagger, or YAML specs
Create Agent Skills with progressive disclosure
Deploy to edge with MCPFusion framework
Built in DLP, auth, and compliance on each call
Real time usage dashboard and cost metering
Publish to catalog or keep private

Start building

Make Your AI Do More

Start with Baserow, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.

Use this MCP plus 5,200+ others, all in one place
Add new capabilities to your AI anytime you want
Connections are secured and governed automatically
Track usage and costs across all your servers
Works with Claude, ChatGPT, Cursor, and more
New servers added to the catalog weekly

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Baserow. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

VINKIUS INFRASTRUCTURE

Cloud Hosted

Managed infra

V8 Isolated

Sandboxed per request

Zero-Trust Proxy

No stored credentials

DLP Enforced

Policy on each call

GDPR Compliant

EU data residency

Token Compression

~60% cost reduction

Your data is protected. See how we built it.

The headache of switching between systems is draining your day. Solved with Vinkius AI Gateway

Today, updating a simple record means opening your primary project management tool, then clicking over to the dedicated database tab. You manually find the right table, locate the row by ID or name, and then carefully update the status field—all while juggling multiple tabs and hoping you don't overwrite something critical.

With this MCP, you simply tell your agent: 'Update Project Gamma's status to Review.' The AI handles all the clicks, the navigation, and the data validation behind the scenes. You get confirmation that the row was successfully updated without ever leaving your conversation window.

Baserow MCP gives you conversational control over structured data.

Manual steps like listing tables, checking field types (`list_fields`), and fetching specific records using `get_row` used to require writing boilerplate code or navigating complex UI menus. Now, your agent runs these operations in the background based on your simple prompt.

It's not just faster; it changes the entire process. You move from being a data operator who executes clicks to a strategic user who directs the flow of information.

Support 24/7 support@vinkius.com ↗

Security Vinkius Trust Center ↗

SLA Service Level Agreement ↗

Report Listing Send Report ↗

no-code

relational-database

data-schema

api-integration

data-orchestration

workspace-management

What your AI can actually do with this

You manage your no-code databases conversationally. This MCP gives your agent full control over structured information housed in Baserow, letting you treat your database like an extension of natural language chat. Instead of navigating through menus or copying raw JSON to update records, you simply ask for what you need.

Your AI client acts as a dedicated data architect, allowing you to list all connected workspaces and applications, manage fields, and even perform complex searches using semantic keywords across tables.

This capability means no more getting lost in spreadsheet tabs. You can programmatically read specific record details or update an entire row's status just by describing the change. Through Vinkius, your agent gains access to thousands of other tools, making it a central hub for all your structured data needs.

Whether you need to create a new project entry, delete old records, or verify account permissions, this MCP handles the underlying complexity so you only deal with the outcome.

Built · Hosted · Managed by Vinkius Baserow MCP - Manage No-Code Databases with AI

Server ID 019dd0c0-7b6e-7396-82db-286f4d96a8ae

Vinkius Inspector

Compliance Grade A+

Score 100/100

Report View Report ↗

What Changes When You Connect

Stop manual data entry. Instead of clicking through forms to update a project status, simply ask your agent to 'Update the row for Project Alpha to Status: Complete.'

Build custom workflows without code. Use the create_row tool to programmatically generate new records—like onboarding a new client or adding inventory items—using natural language prompts.

See exactly what you're working with. The agent can use list_fields to show you every available data point in a table, helping you understand the schema before you write a query.

Never lose track of your systems again. Use list_workspaces or list_applications to get an instant directory of every database managed under your account.

Search smarter, not harder. The agent uses semantic search via list_rows, letting you find records based on keywords rather than needing exact IDs or complex filters.

See it in action

01 01

Auditing Project Status

A PM needs to know the status of all marketing assets. Instead of opening 15 different spreadsheets, they ask their agent: 'List all rows in the Assets table where the Owner is Sarah.' The agent executes list_rows and returns a clean list.

02 02

Onboarding New Vendors

A data analyst needs to input 20 new vendor records. They ask: 'Create 20 rows in the Vendor database with these JSON details.' The agent uses create_row repeatedly, saving hours of manual work.

03 03

Troubleshooting Data Errors

A developer notices a row is missing key data. They ask: 'What are the current fields in the CRM table?' The agent runs list_fields, confirming if the required field even exists before attempting an update.

04 04

Cleaning Up Old Data

A team lead needs to archive old project data. They ask: 'Delete all rows in the Project table where the completion date is over two years ago.' The agent runs delete_row safely, cleaning up the ledger.

The honest tradeoffs

What to watch out for, and the recommended way to handle each one.

Manual Data Transfer

Avoid

Copying a client's name and account number from an email into a separate spreadsheet just to track status changes.

Instead

Instead, ask your agent to 'Update the row for Client XYZ with new contact info.' The agent handles the connection and data transfer using update_row.

Forgetting the Scope

Avoid

Trying to find a specific piece of information but forgetting which database or table it lives in.

Instead

First, run list_workspaces to see all connected systems. Then, use list_tables within the correct workspace to narrow down where you need to look.

Over-Reliance on Formulas

Avoid

Spending time building complex formulas in a spreadsheet just to aggregate data from multiple sources.

Instead

Use your agent to run list_rows with specific search parameters, letting the AI pull and present the aggregated list of records for you.

When It Fits, When It Doesn't

Use this MCP if your core problem involves managing structured, relational data (tables, fields, rows). If you need to read, write, or modify information that lives in a defined database schema, this is your tool. It excels when the process moves from 'Where do I click?' to 'What do I tell my agent?'. Don't use it if your goal is purely conversational messaging (use a dedicated chat API) or if you are dealing with unstructured documents like PDFs (use a document parsing MCP). If you need to design the schema, start by running list_applications and then check the available fields using list_fields. This gives you full visibility into what data structures you can manipulate.

Questions you might have

How do I check which databases Baserow MCP can access? +

You use the list_workspaces tool. This command provides an overview of every high-level workspace connected to your account, letting you know what systems are available for management.

Can I read data from multiple tables at once using Baserow MCP? +

Yes, by combining tools. You first use list_tables to identify all relevant sources, and then ask your agent to run list_rows against each table you need.

What if I don't know the ID of a row I want to update? +

You can use list_rows first. By providing search criteria (like 'Project Name: Alpha'), the agent will find the matching records and give you the necessary IDs before you run update_row.

Does Baserow MCP support large data sets? +

Yes, the tools are designed for scale. The list_rows tool specifically supports pagination and search, meaning it can handle listing many records without timing out.

Give Claude and any AI agent real-world access

What AI agents can do with Baserow MCP: 9 Data Management Tools

List Applications

Shows all distinct Baserow applications (databases) you have set up.

Create Row

Creates a brand new record in any specified table, requiring field names and values...

Delete Row

Permanently removes a specific row from a given table.

List Fields

Retrieves the names and types of all fields available within a chosen table.

Get Row

Fetches detailed data for one specific row, using its unique identifier.

List Rows

Searches and lists multiple rows in a table; supports pagination and search terms.

List Tables

Displays all available tables within a selected database application.

Update Row

Modifies the data in an existing row, requiring both the row's identifier and new...

List Workspaces

Lists every workspace connected to your Baserow account.

Security and governance baked right in.

Claude AI

Open Claude Settings

Add Custom Connector

Start a conversation

Claude Code

Open your terminal

Add the MCP Server

Start coding

Cursor

One-Click Install (Recommended)

Open Cursor Settings

Add New Server

Use in Composer

Antigravity

Configure Agent Environment

Bind the Endpoint

Execute

VS Code Copilot

One-Click Install (Recommended)

Open MCP Settings

Add Server Config

Windsurf

One-Click Install (Recommended)

Open Windsurf Settings

Add Server Endpoint

LangChain

Install Dependencies

Connect the Server

CrewAI

Define the Tool

Execute Task

Choose How to Get Started

Build Your Own

Make Your AI Do More

The headache of switching between systems is draining your day. Solved with Vinkius AI Gateway

Baserow MCP gives you conversational control over structured data.

no-code

relational-database

data-schema

api-integration

data-orchestration

workspace-management

What your AI can actually do with this

Here's how it actually works

Who is this actually for?

What Changes When You Connect

Auditing Project Status

Onboarding New Vendors

Troubleshooting Data Errors

Cleaning Up Old Data

The honest tradeoffs

Manual Data Transfer

Forgetting the Scope

Over-Reliance on Formulas

When It Fits, When It Doesn't

Questions you might have