Query Live Sage X3 Cloud 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 Sage X3 Cloud data. This enables developers to query schemas, retrieve records, and explore Sage X3 Cloud data without leaving the editor or writing custom integration code.

This article explains how to configure Sage X3 Cloud connectivity in Connect AI, register the CData MCP Server in Zed, and query live Sage X3 Cloud data from the Zed agent panel.

Step 1: Configure Sage X3 Cloud connectivity for Zed

Connectivity to Sage X3 Cloud from Zed is made possible through CData Connect AI's Remote MCP Server. To interact with Sage X3 Cloud data from Zed, start by creating and configuring a Sage X3 Cloud connection in CData Connect AI.

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

2. Select Sage X3 Cloud from the Add Connection panel

3. Enter the necessary authentication properties to connect to Sage X3 Cloud.

   Sage X3 Cloud uses the OAuth 2.0 Client Credentials flow, and an X-API-Key is also required for API access. Set AuthScheme to OAuth and specify the following connection properties:

   • URL: The base URL of your Sage X3 Cloud instance.
   • OAuthAccessTokenUrl: The OAuth token endpoint (e.g., https://your-auth-domain/oauth/token).
   • OAuthClientId: Your OAuth application client ID.
   • OAuthClientSecret: Your OAuth application client secret.
   • Audience: The API audience value for the token request.
   • XAPIKey: The X-API-Key provided by your Sage X3 Cloud administrator.
   • Folder: The Sage X3 folder name (e.g., SEED). This folder is used as the default schema.
   • Folders (optional): A comma-separated list of Sage X3 folders (e.g., SEED,PERF). Each folder is exposed as a separate schema, so you can query across folders with the Schema.Table syntax.

   The driver obtains an access token with the Client Credentials flow and sends it with the X-API-Key on every API request. With InitiateOAuth set to GETANDREFRESH (the default), the driver acquires and refreshes the token automatically.

   
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 Sage X3 Cloud connection configured and a PAT generated, Zed can now connect to Sage X3 Cloud 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 Sage X3 Cloud data through Connect AI.

Step 3: Query live Sage X3 Cloud data from the Zed agent

With the integration complete, use the Zed agent panel to explore and interact with live Sage X3 Cloud 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 Sage X3 Cloud
   • Query the top 5 records from a table in Sage X3 Cloud data
3. The agent calls the CData Connect AI MCP Server and returns live results from Sage X3 Cloud data

At this point, your Zed agent communicates with the CData Connect AI MCP Server and retrieves live Sage X3 Cloud data through remote MCP tools directly from the editor.

Get CData Connect AI

To access hundreds of SaaS, Big Data, and NoSQL sources directly from your cloud applications, try CData Connect AI today! Start 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.