How to Query Live Webflow Data in Claude Desktop

Model Context Protocol (MCP) is an emerging, open-source standard for connecting LLMs with external services and data sources. Through MCP Servers, AI clients can perform actions like opening Jira tickets, posting Slack messages, committing GitHub branches and more. With CData MCP Server, these capabilities expand exponentially.

CData MCP Server provides schema-aware context to AI tools — whether you're using it for AI-assisted code generation in IDEs like Cursor, or for querying live data through chat interfaces like Claude Desktop.

In this article, we guide the reader through installing CData API Driver for MCP Server, configuring the connection to Webflow, and asking questions of the data in Claude Desktop.

Prerequisites

You need to download Claude Desktop (download) and create an account before continuing.

Overview

Here's a quick overview of the steps:

1. Download and install the CData API Driver for MCP Server
2. Configure the connection to Webflow
3. Ask questions about the data in Claude Desktop

Step 1: Download and install CData MCP Server

1. To begin, navigate to https://www.cdata.com/solutions/codeassist/ and download the CData API Driver for MCP Server.
2. Find and double-click the installer to begin the installation.
3. Follow the prompts to complete the installation.

When the installation is complete, you are ready to configure MCP Server by connecting to Webflow.

Step 2: Configure the connection to Webflow

1. After installation, the MCP Server configuration wizard should open automatically.

   NOTE: If the wizard does not open automatically, search for "CData MCP Server" in the Windows search bar and double-click the application.

2. Click the dropdown menu in MCP Configuration > Configuration Name and select ""
3. Name the configuration (e.g. "cdataapi") and click "OK."

   NOTE: This name is used as the name for the MCP server and as the prefix for all of the MCP Server's tools.

   

4. Connecting to Webflow

   Authentication

   Webflow uses OAuth 2.0 authentication to ensure secure access to sites, CMS collections, e-commerce data, and other resources. This authentication method allows you to securely connect to your Webflow workspace and manage resources with proper authorization.

   OAuth 2.0 Setup and Configuration

   Step 1: Create a Webflow OAuth Application

   To set up OAuth authentication:

   1. Visit the Webflow Developer Portal
   2. Navigate to "Apps & Integrations" in your Webflow account
   3. Click "Register an App" to create a new OAuth application
   4. Configure the application name, description, and redirect URI (CallbackURL)
   5. Copy the Client ID and Client Secret for use in your connection

   Required Connection Properties

   • AuthScheme: Set this to OAuth (required)
   • OAuthClientId: Client ID from your Webflow OAuth application (required)
   • OAuthClientSecret: Client secret from your Webflow OAuth application (required)
   • CallbackURL: Redirect URI specified in your OAuth application (required)
   • InitiateOAuth: Set to GETANDREFRESH for automatic token management (recommended)

   Required OAuth Scopes

   The Webflow API Profile requires the following OAuth scopes:

   • sites:read - Read access to site information and configuration
   • pages:read - Read access to site pages
   • cms:read - Read access to CMS collections and items
   • forms:read - Read access to forms and form submissions
   • assets:read - Read access to media assets and folders
   • ecommerce:read - Read access to products, orders, and inventory
   • authorized_user:read - Read access to the authorized user

   Enter the appropriate connection properties in the configuration wizard.

   
5. Click "Connect" to authenticate with Webflow through OAuth.

   NOTE: The configuration wizard should open your browser and ask you to sign into Webflow. If your browser does not open, close the configuration wizard and re-open the application using "Run as Administrator" (see below).

   
6. Finally, click "Save Configuration" to save the configuration.

   NOTE: This saves the configuration details to a separate file and updates the Claude Desktop configuration file (claude_desktop_config.json) to start MCP Server when the Claude Desktop client starts.

With MCP Server configured, you are ready to start asking questions of your live data from Claude.

Step 3: Ask AI for answers from live Webflow data

Now that we have installed MCP Server and configured a connection, we are ready to start with Webflow data in Claude Desktop.

1. Open Claude Desktop. It may take a moment for MCP Server to start, but you will see the list of servers and tools available in the Claude interface (look for the settings icon below the prompt bar).

   You can individually enable and disable specific tools by clicking on the server name.

2. Now that you have connected, you can ask Claude questions about the Webflow data. For example: "Can you give me a quantitative analysis about my closed-won opportunities by industry?"

   NOTE: Claude may need to explore the Webflow data to make sense of it before it can begin answering questions of the data. The tabular model presented by CData alongside the database tools available simplify the data exploration and analysis for an LLM.

   

Build with MCP Server. Deploy with CData Drivers.

Download MCP Server for free and give your AI tools schema-aware access to live Webflow data during development. When you're ready to move to production, CData Webflow Drivers deliver the same SQL-based access with enterprise-grade performance, security, and reliability.

Visit the CData Community to share insights, ask questions, and explore what's possible with MCP-powered AI workflows.