Query Live Airtable Data in Zed Editor via CData Connect AI

Zed is a high-performance, open-source code editor built for speed and collaboration. Its built-in AI agent panel supports LLM-powered interactions and MCP (Model Context Protocol) tool integrations, enabling developers to access live external data sources directly within the editor.

By integrating Zed with CData Connect AI through the built-in MCP (Model Context Protocol) Server, the Zed AI agent gains governed, real-time access to live Airtable data. This enables developers to query schemas, retrieve records, and explore Airtable data without leaving the editor or writing custom integration code.

This article walks through configuring Airtable connectivity in Connect AI, registering the CData MCP Server in Zed, and querying live Airtable data from the Zed agent panel.

Step 1: Configure Airtable connectivity for Zed

Connectivity to Airtable from Zed is made possible through CData Connect AI's Remote MCP Server. To interact with Airtable data from Zed, start by creating and configuring a Airtable connection in CData Connect AI.

1. Log into Connect AI, click Sources, and then click Add Connection

2. Select Airtable from the Add Connection panel

3. Enter the necessary authentication properties to connect to Airtable.

   APIKey, BaseId and TableNames parameters are required to connect to Airtable. ViewNames is an optional parameter where views of the tables may be specified.

   • APIKey : API Key of your account. To obtain this value, after logging in go to Account. In API section click Generate API key.
   • BaseId : Id of your base. To obtain this value, it is in the same section as the APIKey. Click on Airtable API, or navigate to https://airtable.com/api and select a base. In the introduction section you can find "The ID of this base is appxxN2ftedc0nEG7."
   • TableNames : A comma separated list of table names for the selected base. These are the same names of tables as found in the UI.
   • ViewNames : A comma separated list of views in the format of (table.view) names. These are the same names of the views as found in the UI.
   
4. Click Save & Test
5. Navigate to the Permissions tab and update user-based permissions

Add a Personal Access Token

A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from Zed. It is best practice to create a separate PAT for each integration to maintain granular access control.

1. Click the gear icon () at the top right of the Connect AI app to open Settings
2. On the Settings page, go to the Access Tokens section and click Create PAT
3. Give the PAT a descriptive name and click Create

4. Copy the token when displayed and store it securely. It will not be shown again

With the Airtable connection configured and a PAT generated, Zed can now connect to Airtable data through Connect AI.

Step 2: Configure Connect AI in Zed

Now, let's register the CData Connect AI MCP endpoint in Zed so that the built-in AI agent can discover and call live data tools.

1. Download and install Zed
2. Open the agent panel by pressing Ctrl + Shift + /, or by clicking the sparkle icon at the bottom right of the editor
3. In the agent panel, click the ... (toggle agent menu) and select Add Custom Server from the dropdown
4. Select the Configure Remote option to configure CData's MCP
5. An Add MCP Server dialog opens displaying a remote server configuration template. Replace the placeholder content with the following JSON:

   {
       "cdata": {
           "url": "https://mcp.cloud.cdata.com/mcp",
           "headers": {
               "Authorization": "Basic your_base64_encoded_email_PAT"
           }
       }
   }
           

   Note: Combine your Connect AI email and PAT in the format email:PAT, Base64 encode the combined string, and prefix it with Basic. For example, given [email protected]:ABC123...XYZ, the header value becomes something like: Basic dXNlckBteWRvbWFpbjphSzkvbVB4Mi9Rcjd2TjQ...

   
6. Click Add Server or press Ctrl + Enter to register the MCP server

Configure an LLM provider

Zed requires at least one LLM provider to power the agent's reasoning. Configure a provider so the agent can interpret queries and call MCP tools through Connect AI.

1. Click the ... (toggle agent menu) and select Settings
2. Under LLM Providers, expand your preferred provider (e.g., Anthropic, OpenAI, Google AI) and enter your API key
3. Under Model Context Protocol (MCP) Servers, confirm that cdata appears with a green dot and the toggle is enabled

With the MCP server registered and an LLM provider configured, the Zed agent is ready to query live Airtable data through Connect AI.

Step 3: Query live Airtable data from the Zed agent

With the integration complete, use the Zed agent panel to explore and interact with live Airtable data through natural language prompts.

1. Open the agent panel using Ctrl + Shift + / and start a new thread
2. Enter a prompt to interact with your data, for example:
   • List all catalogs in my cdata connection
   • Show the available schemas and tables for Airtable
   • Query the top 5 records from a table in Airtable data
3. The agent calls the CData Connect AI MCP Server and returns live results from Airtable data

At this point, your Zed agent communicates with the CData Connect AI MCP Server and retrieves live Airtable data through remote MCP tools directly from the editor.

Get CData Connect AI

To access 300+ SaaS, Big Data, and NoSQL sources directly from your cloud applications, try CData Connect AI today! Download a free 14-day trial of CData Connect AI today, and as always, our world-class Support Team is available to assist you with any questions you may have.