Build RabbitMQ-Powered Applications in Cursor with CData MCP Server

Cursor is an AI-powered code editor that integrates agentic AI into everyday development workflows. With support for MCP, Cursor can connect to local tools and enterprise data sources directly from the editor, enabling natural language interaction with live systems without switching context.

Model Context Protocol (MCP) is an open standard for connecting LLM clients to external services through structured tool interfaces. MCP servers expose capabilities such as schema discovery and live querying, allowing AI agents to retrieve and reason over real-time data safely and consistently.

In this article, we guide you through installing the CData API Driver for MCP Server, configuring the connection to RabbitMQ, connecting the MCP Server add-on to Cursor, and querying live RabbitMQ data from within the editor.

Step 1: Download and install the CData API Driver for MCP Server

1. To begin, download the CData API Driver for MCP Server
2. Find and double-click the installer to begin the installation
3. Run the installer and follow the prompts to complete the installation

When the installation is complete, you are ready to configure your MCP Server add-on by connecting to RabbitMQ.

Step 2: Configure the connection to RabbitMQ

1. After installation, open the CData API Driver for MCP Server configuration wizard

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

   
2. In MCP Configuration > Configuration Name, either select an existing configuration or choose to create a new one
3. Name the configuration (e.g. "cdata_api") and click OK

4. Enter the appropriate connection properties in the configuration wizard

   About RabbitMQ Management HTTP API

   RabbitMQ is an open-source message broker that supports multiple messaging protocols. The RabbitMQ Management HTTP API provides HTTP-based access to management and monitoring data for a RabbitMQ server. The API exposes information about virtual hosts, exchanges, queues, bindings, connections, channels, consumers, users, permissions, policies, and cluster-wide statistics.

   The Management plugin must be enabled on the RabbitMQ server for the HTTP API to be available. By default, the management interface listens on port 15672.

   Using Basic Authentication

   RabbitMQ Management HTTP API uses HTTP Basic authentication. You must supply the username and password of a RabbitMQ management user.

   To enable access to the management API:

   1. Ensure the RabbitMQ Management plugin is enabled on your server (rabbitmq-plugins enable rabbitmq_management).
   2. Use an existing management user or create one with the appropriate management tag (management, policymaker, monitoring, or administrator).
   3. Note the full base URL of your RabbitMQ Management HTTP API (e.g., http://localhost:15672).

   After configuring your RabbitMQ server, set the following connection properties to connect:

   • AuthScheme: Set this to Basic.
   • URL: Set this to the base URL of your RabbitMQ Management HTTP API (e.g., http://localhost:15672).
   • User: Set this to your RabbitMQ management username (e.g., guest).
   • Password: Set this to your RabbitMQ management password.

   Example connection string:

   Profile=C:\profiles\RabbitMQ.apip;AuthScheme=Basic;URL=http://localhost:15672;User=guest;Password=guest;
   

   Available Tables

   The RabbitMQ profile provides access to the following tables:

   • Overview - Cluster-wide statistics and information about the RabbitMQ node
   • Nodes - Information about individual nodes in the RabbitMQ cluster
   • NodeMemory - Detailed memory usage breakdown for a specific cluster node
   • Connections - List of all open AMQP connections to the broker
   • Channels - List of all open AMQP channels across all connections
   • Consumers - List of all consumers registered across all queues
   • Exchanges - List of exchanges declared across all virtual hosts
   • Queues - List of queues declared across all virtual hosts
   • Bindings - List of all bindings between exchanges and queues
   • VirtualHosts - List of virtual hosts configured on the broker
   • VhostPermissions - User permissions within a specific virtual host
   • Users - List of all RabbitMQ users
   • Permissions - Permission records for all users across all virtual hosts
   • TopicPermissions - Topic-level permission records for all users
   • Policies - List of policies applied to queues and exchanges in virtual hosts
   • OperatorPolicies - List of operator policies applied to queues in virtual hosts
   • Parameters - List of component parameters (e.g., federation, shovel) per virtual host
   • GlobalParameters - List of global parameters that apply across all virtual hosts
   • VhostLimits - Resource limits configured for specific virtual hosts
   • UserLimits - Resource limits configured for specific users
   • FeatureFlags - List of feature flags and their enabled/disabled state on the node
   • DeprecatedFeatures - List of deprecated features and their usage state
   • AuthAttempts - Authentication attempt statistics for the node
   • ClusterName - The name of the RabbitMQ cluster
   • WhoAmI - Information about the currently authenticated management user
   • ExchangeBindingsSource - Bindings for which a specific exchange is the source
   • ExchangeBindingsDestination - Bindings for which a specific exchange is the destination
   • QueueBindings - Bindings for a specific queue within a virtual host
   
5. Click Connect to authenticate with RabbitMQ
6. Then, click Save Configuration to save the MCP Server add-on

This process creates a .mcp configuration file that Cursor will reference when launching the MCP Server add-on. Now with your MCP Server add-on configured, you are ready to connect it to Cursor.

Step 3: Connect the MCP Server add-on to Cursor

1. Download the Cursor desktop application and complete the sign-up flow for your account
2. From the top menu, click Settings to open the settings panel
3. In the left navigation, open the Tools & MCP tab and click Add Custom MCP

Option 1: Manually add the MCP configuration

1. Cursor opens an mcp.json file in the editor
2. Add the code shown below and save the file

{
  "mcpServers": {
    "cdata-local": {
      "command": "C:/Program Files/Java/jdk-17/bin/java.exe",
      "args": [
        "-jar",
        "C:/Program Files/CData/CData API Driver for MCP Server/lib/cdata.mcp.api.jar",
        "cdata_api"
      ]
    }
  }
}



NOTE: The command value should point to your Java 17+ java.exe executable, and the JAR path should point to the installed CData MCP Server add-on .jar file. The final argument must match the MCP configuration name you saved in the CData configuration wizard (e.g. "cdata_api").

Option 2: Copy the MCP configuration from the CData API Driver for MCP Server UI

1. After saving and testing your connection in the configuration wizard, click Next

2. Select Cursor from the AI MCP Tool dropdown

3. Follow the MCP Client Instructions to create the required folders for the MCP config

4. Copy the displayed JSON code and paste it into your configuration file
5. In Cursor, open the project folder you created with the mcp.json config
4. The MCP Server add-on should appear as Running under Installed MCP Servers

Step 4: Query live RabbitMQ data in Cursor

1. From the top bar, click Toggle AI Pane to open the chat window
2. Ask questions about your RabbitMQ data using natural language. For example:

   "List all tables available in my RabbitMQ data connection."

   

Cursor is now fully integrated with CData API Driver for MCP Server and can use the MCP tools exposed to explore schemas and execute live queries against RabbitMQ.

Build with MCP Server. Deploy with CData Drivers.

Download MCP Server for free and give your AI tools schema-aware access to live RabbitMQ data during development. When you're ready to move to production, CData RabbitMQ 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.