How to Connect to Live JSON Services in n8n Workflows and Agents (via CData Connect AI)

n8n is an open-source workflow automation tool that allows you to connect various applications and services to automate tasks and processes. When combined with CData Connect AI Remote MCP, you can leverage n8n to interact with your JSON services in real-time. This article outlines the process of connecting to JSON using Connect AI Remote MCP and creating a basic workflow in n8n to interact with your JSON services.

CData Connect AI offers a dedicated cloud-to-cloud interface for connecting to JSON services. The CData Connect AI Remote MCP Server enables secure communication between n8n and JSON. This allows you to ask questions and take actions on your JSON services using n8n, all without the need for data replication to a natively supported database. With its inherent optimized data processing capabilities, CData Connect AI efficiently channels all supported SQL operations, including filters and JOINs, directly to JSON. This leverages server-side processing to swiftly deliver the requested JSON services.

In this article, we show how to build a simple chat agent in n8n to conversational explore (or Vibe Query) your data. The connectivity principals apply to any n8n workflow. With Connect AI you can build workflows and agents with access to live JSON services, plus hundreds of other sources.

Step 1: Configure JSON Connectivity for n8n

Connectivity to JSON from n8n is made possible through CData Connect AI Remote MCP. To interact with JSON services from n8n, we start by creating and configuring a JSON connection in CData Connect AI.

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

2. Select "JSON" from the Add Connection panel

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

   See the Getting Started chapter in the data provider documentation to authenticate to your data source: The data provider models JSON APIs as bidirectional database tables and JSON files as read-only views (local files, files stored on popular cloud services, and FTP servers). The major authentication schemes are supported, including HTTP Basic, Digest, NTLM, OAuth, and FTP. See the Getting Started chapter in the data provider documentation for authentication guides.

   After setting the URI and providing any authentication values, set DataModel to more closely match the data representation to the structure of your data.

   The DataModel property is the controlling property over how your data is represented into tables and toggles the following basic configurations.

   • Document (default): Model a top-level, document view of your JSON data. The data provider returns nested elements as aggregates of data.
   • FlattenedDocuments: Implicitly join nested documents and their parents into a single table.
   • Relational: Return individual, related tables from hierarchical data. The tables contain a primary key and a foreign key that links to the parent document.

   See the Modeling JSON Data chapter for more information on configuring the relational representation. You will also find the sample data used in the following examples. The data includes entries for people, the cars they own, and various maintenance services performed on those cars.

   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add JSON Connection page and update the User-based permissions.

Add a Personal Access Token

A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from n8n. It is best practice to create a separate PAT for each service to maintain granularity of access.

1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create.
4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured and a PAT generated, we are ready to connect to JSON services from n8n.

Step 2: Connect n8n to CData Connect AI

Follow these steps to connect to CData Connect AI in n8n:

1. Sign in to n8n.io or create a new account.
2. Create a Workflow in n8n that uses the MCP Client tool. The example Workflow below acts as a chatbot. OpenAI was used as the Chat Model, and Simple Memory was used for the Memory.
3. Configure the MCP Client node in the Workflow:
   • Set Endpoint to https://mcp.cloud.cdata.com/mcp (found in the "Connect Data to AI" ribbon in Connect AI)
   • Set Server Transport to HTTP Streamable
   • Set Authentication to Header Auth and set the following properties to use Basic authentication:
     • Set Name to Authorization
     • Set Value to Basic EMAIL:PAT, replacing the EMAIL and PAT with your Connect AI email address and the PAT created previously. For example: Basic [email protected]:Uu90pt5vEO..."
     
   

Optional Step: Give the AI Agent context

This step establishes the AI Agent's role and provides context for the conversation through the System Message parameter in the AI Agent node. By providing a system message that explicitly informs the agent about its role as an MCP Server expert and lists the available tools, you can enhance the agent's understanding and response accuracy. For example, you can set the System Message to:

You are an expert at using the MCP Client tool connected which is the CData Connect AI MCP Server. Always search thoroughly and use the most relevant MCP Client tool for each query. Below are the available tools and a description of each:
queryData: Execute SQL queries against connected data sources and retrieve results. When you use the queryData tool, ensure you use the following format for the table name: catalog.schema.tableName
getCatalogs: Retrieve a list of available connections from CData Connect AI. The connection names should be used as catalog names in other tools and in any queries to CData Connect AI. Use the `getSchemas` tool to get a list of available schemas for a specific catalog.
getSchemas: Retrieve a list of available database schemas from CData Connect AI for a specific catalog. Use the `getTables` tool to get a list of available tables for a specific catalog and schema.
getTables: Retrieve a list of available database tables from CData Connect AI for a specific catalog and schema. Use the `getColumns` tool to get a list of available columns for a specific table.
getColumns: Retrieve a list of available database columns from CData Connect AI for a specific catalog, schema, and table.
getProcedures: Retrieve a list of stored procedures from CData Connect AI for a specific catalog and schema
getProcedureParameters: Retrieve a list of stored procedure parameters from CData Connect AI for a specific catalog, schema, and procedure.
executeProcedure: Execute stored procedures with parameters against connected data sources
  

Step 3: Explore Live JSON Services with n8n

With the Workflow created in n8n and the MCP Client connected, you can now interact with your JSON services using n8n. The MCP Client node allows you to send queries and receive responses from the JSON data source in real-time.

Open the Workflow in n8n and execute it to start interacting with your JSON services. You can ask questions, retrieve data, and perform actions on your JSON services using the MCP Client node:

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