Build an MCP server with Airtable

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2/3/2026

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Who is this for?

This template is designed for anyone who wants to integrate MCP with their AI Agents using Airtable. Whether you're a developer, a data analyst, or an automation enthusiast, if you're looking to leverage the power of MCP and Airtable in your n8n workflows, this template is for you.

What problem is this workflow solving?

This template caters to MCP beginners seeking a hands-on example and developers looking to integrate Airtable MCP service. When integrating MCP with Airtable, manually updating AI Agents after changes to Airtable data on the MCP Server is time-consuming and error-prone.

This template automates the process, enabling the AI Agent to instantly recognize changes made to Airtable on the MCP Server. In data management, for example, it ensures that record updates or additions in Airtable are automatically detected by the AI Agent. With detailed steps, it simplifies the integration process for all users.

What this workflow does

This workflow focuses on integrating MCP with Airtable within n8n. Specifically, it allows you to build an MCP Server and Client using Airtable nodes in n8n. Any changes made to the Airtable Base/Table on the MCP Server are automatically recognized by the MCP Client in the workflow. This means that you can make changes to your Airtable (such as adding, deleting, or modifying records) on the MCP Server, and the MCP Client in the n8n workflow will immediately detect these changes without any manual intervention.

Setup

Requirements

An active n8n account. Access to Airtable API. A sample base and rows in Airtable that you can use to test. An API key from your preferred LLM to power the AI agent.

Step-by-step guide

Create a new workflow in n8n: Log in to your n8n account and create a new workflow.
Add Airtable nodes: Search for and add the Airtable nodes to your workflow that you wish the MCP client to have access to.
Set up the MCP Server and Client: Use the appropriate nodes in n8n to set up the MCP Server and Client. Connect the Airtable nodes to the MCP nodes as required.
Activate and test the workflow: Talk to the chat trigger once all credentials have been updated and table data synced and try adding some rows, deleting or finding and updating cells.

How to customize this workflow to your needs

If you want to customize this workflow, you can:

Modify the triggers: You can change the conditions under which the MCP Client detects changes. For example, you can set it to detect changes only in specific fields or based on certain record values in Airtable.
Integrate with other services: You can add more nodes to the workflow to integrate with other services, such as sending notifications to Slack or triggering further actions based on the detected Airtable changes.

Need help?

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Build an MCP Server with AI Agent and OpenAI Chat Model

This n8n workflow demonstrates how to set up a Model Context Protocol (MCP) server that leverages an AI Agent powered by an OpenAI Chat Model and a simple memory to respond to incoming chat messages. This allows you to expose an intelligent agent that can maintain conversational context.

What it does

Listens for MCP Chat Messages: The workflow is triggered by incoming chat messages via the MCP Server Trigger.
Initializes Simple Memory: A Simple Memory node is used to maintain conversational context across messages, allowing the AI agent to remember previous interactions.
Configures OpenAI Chat Model: An OpenAI Chat Model node is set up to provide the underlying language model for the AI agent's responses.
Processes with AI Agent: An AI Agent node receives the incoming chat message and the conversational memory. It uses the OpenAI Chat Model to generate a relevant response, taking into account the conversation history.
Sends Response via MCP Client: The AI Agent's response is then sent back to the client using the MCP Client Tool node.

Prerequisites/Requirements

n8n Instance: An active n8n instance.
OpenAI API Key: An API key from OpenAI to use their Chat Model. This will need to be configured as a credential in n8n.
LangChain Nodes: Ensure the @n8n/n8n-nodes-langchain package is installed and enabled in your n8n instance.

Setup/Usage

Import the Workflow: Import the provided JSON into your n8n instance.
Configure OpenAI Credentials:
- Find the "OpenAI Chat Model" node.
- Click on the "Credentials" field and select or create a new "OpenAI API" credential.
- Enter your OpenAI API Key.
Activate the Workflow: Once the credentials are set, activate the workflow.
Interact with the MCP Server: Your n8n instance will now be running an MCP server. You can send chat messages to it using an MCP client, and the AI agent will respond. The exact URL for the MCP server will be visible in the "MCP Server Trigger" node after activation.

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