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

Integrate Flowise AI with the CData Connect AI MCP Server to enable agents to securely query and act on live data without replication.

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 Odoo 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 Odoo 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 Odoo data in real time.

About Odoo Data Integration

Accessing and integrating live data from Odoo has never been easier with CData. Customers rely on CData connectivity to:

Access live data from both Odoo API 8.0+ and Odoo.sh Cloud ERP.
Extend the native Odoo features with intelligent handling of many-to-one, one-to-many, and many-to-many data properties. CData's connectivity solutions also intelligently handle complex data properties within Odoo. In addition to columns with simple values like text and dates, there are also columns that contain multiple values on each row. The driver decodes these kinds of values differently, depending upon the type of column the value comes from:
- Many-to-one columns are references to a single row within another model. Within CData solutions, many-to-one columns are represented as integers, whose value is the ID to which they refer in the other model.
- Many-to-many columns are references to many rows within another model. Within CData solutions, many-to-many columns are represented as text containing a comma-separated list of integers. Each value in that list is the ID of a row that is being referenced.
- One-to-many columns are references to many rows within another model - they are similar to many-to-many columns (comma-separated lists of integers), except that each row in the referenced model must belong to only one in the main model.
Use SQL stored procedures to call server-side RFCs within Odoo.

Users frequently integrate Odoo with analytics tools such as Power BI and Qlik Sense, and leverage our tools to replicate Odoo data to databases or data warehouses.

Getting Started

Step 1: Configure Odoo Connectivity for Flowise

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

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

Select Odoo from the Add Connection panel

Enter the necessary authentication properties to connect to Odoo.
To connect, set the Url to a valid Odoo site, User and Password to the connection details of the user you are connecting with, and Database to the Odoo database.
Click Save & Test
Navigate to the Permissions tab and update user-based permissions

Once the connection is established, Odoo 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 Odoo connection configured and a PAT generated, Flowise AI can now connect to Odoo data through the CData MCP Server.

Step 2: Configure Connect AI credentials in Flowise AI

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 Odoo data in Flowise

Open the Chat tab in Flowise
Type a query such as "Show top 10 records from Odoo 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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