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Mistral AI is a frontier AI company that builds enterprise-grade open-source and commercial large language models (LLMs). With Mistral, you can train, fine-tune, and deploy agents anywhere β on premises, in the cloud, or at the edge β while retaining full control of your data. Its agent-ready platform enables multilingual and multimodal AI that can search, create, code, automate, and collaborate securely, with support for memory and extended context handling.
CData Connect AI provides a secure cloud-to-cloud interface for easily integrating hundreds of enterprise data sources with Mistral AI. Through CData Connect AI, Mistral AI agents can query, analyze, and act on live MongoDB data in real time, without replication. Connect AI manages authentication, security, and query optimization so you can focus on building intelligent workflows, while Mistral handles reasoning and natural language interaction.
In this guide, we will use Mistral AI's Le Chat, Mistral's customizable conversational chatbot, along with CData Connect AI to connect to live MongoDB data. You will be able to interact with your live MongoDB data directly in Mistral AI workflows β running queries and automating tasks securely.
The setup takes just a few minutes, and once connected, you will have your own chatbot agent intelligently conversing with your live MongoDB data.
Let's begin.
Here is a quick overview of the steps we will follow:
Accessing and integrating live data from MongoDB has never been easier with CData. Customers rely on CData connectivity to:
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.
Connectivity to MongoDB from Mistral AI is made possible through CData Connect AI Remote MCP. To interact with MongoDB data from Mistral, we start by creating and configuring a MongoDB connection in CData Connect AI.
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.
π Configuring a connection (Salesforce is shown)A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from Mistral AI. It is a best practice to create a separate PAT for each service to maintain fine-grained access control.
With the connection configured and a PAT generated, you are ready to connect to MongoDB data from Mistral AI workflows.
With your MongoDB connection and PAT created in CData Connect AI, the next step is to configure a custom MCP connector inside Mistral Le Chat.
This step ensures that Mistral Le Chat can securely route queries through the CData Remote MCP Server to your live MongoDB data.
Now that your MCP connector is configured in Le Chat, you can begin querying live MongoDB data directly in your conversations.
And that's it! You can now interact with live MongoDB data conversationally inside Mistral Le Chat.
With the integration complete, you can go beyond simple queries and build complex, multi-step AI agents. These agents can combine reasoning from Mistral AI with secure, real-time access to your enterprise data through CData Connect AI, enabling workflows such as sales forecasting, support triage, customer trend analysis, and more.
Try CData Connect AI for free today and use the full power of Mistral AI agents with secure, live access to your enterprise data.
Learn more about CData Connect AI or sign up for free trial access:
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