How to Connect Flowise AI Agents to Live Presto 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 over 350+ enterprise data sources. Through its Model Context Protocol (MCP) server, CData Connect AI bridges Flowise agents with live Presto 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 Presto 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 Presto data in real time.
About Presto Data Integration
Accessing and integrating live data from Trino and Presto SQL engines has never been easier with CData. Customers rely on CData connectivity to:
- Access data from Trino v345 and above (formerly PrestoSQL) and Presto v0.242 and above (formerly PrestoDB)
- Read and write access all of the data underlying your Trino or Presto instances
- Optimized query generation for maximum throughput.
Presto and Trino allow users to access a variety of underlying data sources through a single endpoint. When paired with CData connectivity, users get pure, SQL-92 access to their instances, allowing them to integrate business data with a data warehouse or easily access live data directly from their preferred tools, like Power BI and Tableau.
In many cases, CData's live connectivity surpasses the native import functionality available in tools. One customer was unable to effectively use Power BI due to the size of the datasets needed for reporting. When the company implemented the CData Power BI Connector for Presto they were able to generate reports in real-time using the DirectQuery connection mode.
Getting Started
Step 1: Configure Presto Connectivity for Flowise
Connectivity to Presto from Flowise AI is made possible through CData Connect AI's Remote MCP Server. To interact with Presto data from Flowise AI, we start by creating and configuring a Presto connection in CData Connect AI.
- Log into Connect AI, click Sources, and then click Add Connection
- Select Presto from the Add Connection panel
-
Enter the necessary authentication properties to connect to Presto.
Set the Server and Port connection properties to connect, in addition to any authentication properties that may be required.
To enable TLS/SSL, set UseSSL to true.
Authenticating with LDAP
In order to authenticate with LDAP, set the following connection properties:
- AuthScheme: Set this to LDAP.
- User: The username being authenticated with in LDAP.
- Password: The password associated with the User you are authenticating against LDAP with.
Authenticating with Kerberos
In order to authenticate with KERBEROS, set the following connection properties:
- AuthScheme: Set this to KERBEROS.
- KerberosKDC: The Kerberos Key Distribution Center (KDC) service used to authenticate the user.
- KerberosRealm: The Kerberos Realm used to authenticate the user with.
- KerberosSPN: The Service Principal Name for the Kerberos Domain Controller.
- KerberosKeytabFile: The Keytab file containing your pairs of Kerberos principals and encrypted keys.
- User: The user who is authenticating to Kerberos.
- Password: The password used to authenticate to Kerberos.
- Click Save & Test
- Navigate to the Permissions tab and update user-based permissions
Once the connection is established, Presto 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.
- Click the gear icon () at the top right of the Connect AI app to open Settings
- On the Settings page, go to the Access Tokens section and click Create PAT
- Give the PAT a descriptive name and click Create
- Copy the token when displayed and store it securely. It will not be shown again
With the Presto connection configured and a PAT generated, Flowise AI can now connect to Presto data through the CData MCP Server.
Step 2: Configure Connect AI credentials in Flowise AI
Log in to Flowise AI workspace to set up the integration.
Add OpenAI credentials
- Navigate to Credentials and choose Add Credential
- Select OpenAI API from the dropdown
- Provide a name (e.g., OpenAI_Key) and paste the API key
Add the PAT variable
- Navigate to Variables and Add Variable
- Set Variable Name (e.g., PAT), choose Static as type, and set the Value to Base64-encoded username:PAT
- Click Add to save the variable
Step 3: Build the agent in Flowise AI
- Go to Agent Flows, select Add New
- Click the "+" icon to add a new node and choose Agent and drag the agent to the workflow
- 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
- Under Tools, click Add Tool and choose Custom MCP
- 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 Presto data in Flowise
- Open the Chat tab in Flowise
- Type a query such as "Show top 10 records from Presto data table"
- 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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