How to Connect Flowise AI Agents to Live Neo4J Data via CData Connect AI

Flowise AI is an open-source, no-code tool for building AI workflows and custom agents visually. Its drag-and-drop interface allows you to integrate large language models (LLMs) with APIs, databases, and external systems effortlessly.

CData Connect AI enables real-time connectivity to hundreds of enterprise data sources. Through its Model Context Protocol (MCP) server, CData Connect AI bridges Flowise agents with live Neo4J securely and efficiently, no data replication required. By combining Flowise AI's intuitive agent builder with CData's MCP integration, users can create agents capable of fetching, analyzing, and acting upon live Neo4J data directly within Flowise AI workflows.

This guide shows you how to connect Flowise AI to CData Connect AI MCP, set up credentials, and enable your agents to query live Neo4J data in real time.

Step 1: Configure Neo4J Connectivity for Flowise

Connectivity to Neo4J from Flowise AI is made possible through CData Connect AI's Remote MCP Server. To interact with Neo4J data from Flowise AI, we start by creating and configuring a Neo4J connection in CData Connect AI.

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

2. Select Neo4J from the Add Connection panel

3. Enter the necessary authentication properties to connect to Neo4J.

   To connect to Neo4j, set the following connection properties:

   • Server: The server hosting the Neo4j instance.
   • Port: The port on which the Neo4j service is running. The provider connects to port 7474 by default.
   • User: The username of the user using the Neo4j instance.
   • Password: The password of the user using the Neo4j instance.
   
4. Click Save & Test
5. Navigate to the Permissions tab and update user-based permissions

Once the connection is established, Neo4J data is now accessible in CData Connect AI and ready to be used with MCP enabled tools.

Add a Personal Access Token

A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from Flowise AI. 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 Neo4J connection configured and a PAT generated, Flowise AI can now connect to Neo4J data through Connect AI.

Step 2: Configure Connect AI credentials in Flowise AI

Log in to Flowise AI workspace to set up the integration.

Add OpenAI credentials

1. Navigate to Credentials and choose Add Credential

2. Select OpenAI API from the dropdown
3. Provide a name (e.g., OpenAI_Key) and paste the API key

Add the PAT variable

1. Navigate to Variables and Add Variable

2. Set Variable Name (e.g., PAT), choose Static as type, and set the Value to Base64-encoded username:PAT
3. Click Add to save the variable

Step 3: Build the agent in Flowise AI

1. Go to Agent Flows, select Add New

2. Click the "+" icon to add a new node and choose Agent and drag the agent to the workflow

3. Connect the Start node to the Agent node

Configure agent settings

Double-click on the Agent node and fill in the details:

• Model: select ChatOpenAI or preferred model (e.g., gpt-4o-mini)
• Connect Credential: Select OpenAI API key credential which was created earlier
• Streaming: Enabled

Add the custom MCP tool

1. Under Tools, click Add Tool and choose Custom MCP
2. Fill in the JSON parameters as shown below:

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

Click the refresh icon to load available MCP actions. Once actions are listed, now Flowise agent is successfully connected to CData Connect AI MCP.

Step 4: Test and query live Neo4J data in Flowise

1. Open the Chat tab in Flowise
2. Type a query such as "Show top 10 records from Neo4J data table"
3. Observe that responses are fetched in real time via the CData Connect AI MCP connection

With the workflow run completed, Flowise demonstrates successful retrieval of Salesforce data through the CData Connect AI MCP server, with the MCP Client node providing the ability to ask questions, retrieve records, and perform actions on the data.

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