How to Connect Flowise AI Agents to Live MongoDB 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 MongoDB 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 MongoDB 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 MongoDB data in real time.
About MongoDB Data Integration
Accessing and integrating live data from MongoDB has never been easier with CData. Customers rely on CData connectivity to:
- Access data from MongoDB 2.6 and above, ensuring broad usability across various MongoDB versions.
- Easily manage unstructured data thanks to flexible NoSQL (learn more here: Leading-Edge Drivers for NoSQL Integration).
- Leverage feature advantages over other NoSQL drivers and realize functional benefits when working with MongoDB data (learn more here: A Feature Comparison of Drivers for NoSQL).
MongoDB's flexibility means that it can be used as a transactional, operational, or analytical database. That means CData customers use our solutions to integrate their business data with MongoDB or integrate their MongoDB data with their data warehouse (or both). Customers also leverage our live connectivity options to analyze and report on MongoDB directly from their preferred tools, like Power BI and Tableau.
For more details on MongoDB use case and how CData enhances your MongoDB experience, check out our blog post: The Top 10 Real-World MongoDB Use Cases You Should Know in 2024.
Getting Started
Step 1: Configure MongoDB Connectivity for Flowise
Connectivity to MongoDB from Flowise AI is made possible through CData Connect AI's Remote MCP Server. To interact with MongoDB data from Flowise AI, we start by creating and configuring a MongoDB connection in CData Connect AI.
- Log into Connect AI, click Sources, and then click Add Connection
- Select MongoDB from the Add Connection panel
-
Enter the necessary authentication properties to connect to MongoDB.
Set the Server, Database, User, and Password connection properties to connect to MongoDB. To access MongoDB collections as tables you can use automatic schema discovery or write your own schema definitions. Schemas are defined in .rsd files, which have a simple format. You can also execute free-form queries that are not tied to the schema.
- Click Save & Test
- Navigate to the Permissions tab and update user-based permissions
Once the connection is established, MongoDB 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 MongoDB connection configured and a PAT generated, Flowise AI can now connect to MongoDB 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 MongoDB data in Flowise
- Open the Chat tab in Flowise
- Type a query such as "Show top 10 records from MongoDB 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.
Get CData Connect AI
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