How to Connect to Live Bitbucket Data in Mistral AI Workflows and Agents (via CData Connect AI)

Mohsin Turki
Mohsin Turki
Technical Marketing Engineer
Leverage the CData Connect AI Remote MCP Server to enable Mistral AI to securely access, query, and take action on live Bitbucket data without replication.

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 – on premises, in the cloud, or at the edge – 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 Bitbucket 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 Bitbucket data. You will be able to interact with your live Bitbucket data directly in Mistral AI workflows – 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 Bitbucket data.

Let's begin.

Prerequisites

  1. A Mistral AI account – Sign up or log in here.
  2. A CData Connect AI account – Sign up or log in here.
  3. An active Bitbucket account with valid credentials.

Overview

Here is a quick overview of the steps we will follow:

  1. Connect: Add a connection to Bitbucket in CData Connect AI using your credentials.
  2. Configure: Create a custom MCP connection in Mistral AI Le Chat that points to your Bitbucket connection in CData Connect AI.
  3. Query: Interact with live Bitbucket data in Mistral AI workflows – running queries and taking actions using natural language.

Step 1: Configure Bitbucket Connectivity for Mistral

Connectivity to Bitbucket from Mistral AI is made possible through CData Connect AI Remote MCP. To interact with Bitbucket data from Mistral, we start by creating and configuring a Bitbucket connection in CData Connect AI.

  1. Log into Connect AI, click Sources, and then click Add Connection.
  2. Adding a Connection
  3. Select "Bitbucket" from the Add Connection panel.
  4. Selecting a data source
  5. Enter the necessary authentication properties to connect to Bitbucket.

    For most queries, you must set the Workspace. The only exception to this is the Workspaces table, which does not require this property to be set, as querying it provides a list of workspace slugs that can be used to set Workspace. To query this table, you must set Schema to 'Information' and execute the query SELECT * FROM Workspaces>.

    Setting Schema to 'Information' displays general information. To connect to Bitbucket, set these parameters:

    • Schema: To show general information about a workspace, such as its users, repositories, and projects, set this to Information. Otherwise, set this to the schema of the repository or project you are querying. To get a full set of available schemas, query the sys_schemas table.
    • Workspace: Required if you are not querying the Workspaces table. This property is not required for querying the Workspaces table, as that query only returns a list of workspace slugs that can be used to set Workspace.

    Authenticating to Bitbucket

    Bitbucket supports OAuth authentication only. To enable this authentication from all OAuth flows, you must create a custom OAuth application, and set AuthScheme to OAuth.

    Be sure to review the Help documentation for the required connection properties for you specific authentication needs (desktop applications, web applications, and headless machines).

    Creating a custom OAuth application

    From your Bitbucket account:

    1. Go to Settings (the gear icon) and select Workspace Settings.
    2. In the Apps and Features section, select OAuth Consumers.
    3. Click Add Consumer.
    4. Enter a name and description for your custom application.
    5. Set the callback URL:
      • For desktop applications and headless machines, use http://localhost:33333 or another port number of your choice. The URI you set here becomes the CallbackURL property.
      • For web applications, set the callback URL to a trusted redirect URL. This URL is the web location the user returns to with the token that verifies that your application has been granted access.
    6. If you plan to use client credentials to authenticate, you must select This is a private consumer. In the driver, you must set AuthScheme to client.
    7. Select which permissions to give your OAuth application. These determine what data you can read and write with it.
    8. To save the new custom application, click Save.
    9. After the application has been saved, you can select it to view its settings. The application's Key and Secret are displayed. Record these for future use. You will use the Key to set the OAuthClientId and the Secret to set the OAuthClientSecret.
    Configuring a connection (Salesforce is shown)
  6. Click Save & Test.
  7. Navigate to the Permissions tab in the Add Bitbucket Connection page and update the user-based permissions. Updating permissions

Add a Personal Access Token

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.

  1. Click on the gear icon () at the top right of the Connect AI app to open the Settings page.
  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. Creating a new PAT
  4. Note: The PAT is only visible at creation, so be sure to copy and store it securely for future use.

With the connection configured and a PAT generated, you are ready to connect to Bitbucket data from Mistral AI workflows.


Step 2: Configure the MCP Connector in Mistral Le Chat

With your Bitbucket connection and PAT created in CData Connect AI, the next step is to configure a custom MCP connector inside Mistral Le Chat.

  1. Log into Le Chat. Logging into Mistral Le Chat
  2. From the left-hand menu, click on Intelligence, then select Connectors. Click Add Connector. Adding a new connector
  3. In the dialog, select Custom MCP Connector and enter the following details:
    • Connector Name: For example, CData_Remote_MCP.
    • Connector Server: https://mcp.cloud.cdata.com/mcp (found in the "Connect Data to AI" ribbon in Connect AI).
    • Authentication Method: API Token Authentication.
    • Header Name: Authorization.
    • Header Value: Basic [email protected]:YourPAT (replace "[email protected]" with your CData Connect AI email and "YourPAT" with the PAT created earlier in above format).
    Configuring the MCP connection
  4. Click Connect to establish the connection.
  5. Scroll down to the bottom of the Connections section to confirm that your MCP connection is successfully established. MCP connection established

This step ensures that Mistral Le Chat can securely route queries through the CData Remote MCP Server to your live Bitbucket data.


Step 3: Query Live Bitbucket Data from Mistral AI

Now that your MCP connector is configured in Le Chat, you can begin querying live Bitbucket data directly in your conversations.

  1. In Le Chat, click on Chats in the left menu to start a new chat.
  2. Enable your MCP connector by clicking the Enable Tools button. Enabling MCP tools in Le Chat
  3. Run a discovery query such as Get Catalogs or Get Tables to see the available data sources and schemas connected through CData Connect AI. Listing connected catalogs and tables
  4. Test the connection by running a simple query. For example: "Compare the win rate of Opportunities across different industries." Viewing visual query results (Salesforce is shown) Viewing tabular query results (Salesforce is shown)

And that's it! You can now interact with live Bitbucket data conversationally inside Mistral Le Chat.


Build Complex AI Agents with CData Connect AI

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.

Ready to get started?

Learn more about CData Connect AI or sign up for free trial access:

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