Interact with Live Bitbucket Data in Warp via CData Connect AI

Yazhini G
Yazhini G
Technical Marketing Engineer
Use the CData Connect AI Remote MCP Server to let Warp securely interact with live Bitbucket data directly from the terminal and agent workflow.

Warp is an agentic development environment that combines a modern terminal with an AI agent. It supports large language model (LLM) interactions and Model Context Protocol (MCP) server integrations, so the agent can reach live external data sources without leaving the terminal.

By integrating Warp with CData Connect AI through its built-in MCP Server, the Warp Agent gets governed, real-time access to live Bitbucket data. You can explore Bitbucket data, ask questions in plain language, and work with your records without writing custom integration code.

This article walks through configuring Bitbucket connectivity in Connect AI, configuring the CData MCP Server in Warp, and interacting with live Bitbucket data from the Warp Agent.

Step 1: Configure Bitbucket connectivity for Warp

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

  1. Log into Connect AI, click Sources, and then click Add Connection
  2. Adding a connection in Connect AI
  3. Select Bitbucket from the Add Connection panel
  4. Selecting 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 and update user-based permissions
  8. Updating permissions

Add a Personal Access Token

A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from Warp. It is best practice to create a separate PAT for each integration to maintain granular access control.

  1. Click the gear icon () at the top right of the Connect AI app to open Settings
  2. On the Settings page, go to the Personal Access Tokens section and click Create PAT
  3. Give the PAT a descriptive name and click Create
  4. Creating a new PAT
  5. Copy the token when displayed and store it securely. It will not be shown again

With the Bitbucket connection configured and a PAT generated, Warp can now connect to Bitbucket data through Connect AI.

Step 2: Configure Connect AI in Warp

Enable the Warp Agent, configure an LLM provider, and the Connect AI MCP endpoint in Warp so the agent can discover and call live data tools.

  1. Download and install Warp, and then sign up or log in to your Warp account
  2. Click the Tabs panel icon at the top left of the window, or press Ctrl + Shift + B Opening the Tabs panel in Warp
  3. Click Settings, expand Agents, select Warp Agent, and toggle Warp Agent on Enabling the Warp Agent in Settings

Configure an LLM provider

The Warp Agent needs an LLM provider to interpret your prompts and decide which MCP tools to call. Add an API key for your preferred provider.

  1. On the same Warp Agent page, scroll down to the Custom Inference section
  2. Enter the API key for the LLM provider of your choice (e.g., OpenAI, Anthropic, or Google) Adding an LLM API key under Custom Inference

Add the Connect AI MCP Server

  1. Under Agents, click MCP servers, and then click Add Adding a new MCP server in Warp
  2. In the Add New MCP Server editor, paste the following JSON configuration:
    {
      "mcpServers": {
        "CData_Connect_AI": {
          "url": "https://mcp.cloud.cdata.com/mcp",
          "headers": {
            "Authorization": "Basic your_base64_encoded_email_PAT"
          }
        }
      }
    }

    Note: Combine your Connect AI email and PAT in the format email:PAT, Base64 encode the combined string, and prefix it with Basic. For example, given [email protected]:ABC123...XYZ, the header value becomes something like: Basic dXNlckBteWRvbWFpbjphSzkvbVB4Mi9Rcjd2TjQ...

    Configuring Connect AI MCP Server
  3. Click Save to add the MCP server
  4. Under My MCPs, confirm that CData_Connect_AI appears with the toggle enabled and the tools available Verifying the Connect AI MCP Server is enabled in Warp

With the MCP server and an LLM provider configured, the Warp Agent is ready to interact with live Bitbucket data through Connect AI.

Step 3: Interact with live Bitbucket data from the Warp Agent

Use natural language prompts in the Warp Agent to explore live Bitbucket data.

  1. Click the icon in the left navigation bar and select Agent Starting a new agent conversation in Warp
  2. Enter a prompt to interact with your data, for example:
    • List the sources available in my CData_Connect_AI mcp connection
    • Show me what I can explore in Bitbucket
    • Fetch the five most recent records from Bitbucket data
    Entering a prompt in the Warp Agent
  3. The agent calls the Connect AI MCP Server and returns live results from Bitbucket data Interacting with live data from the Warp Agent

Your Warp Agent now calls the Connect AI MCP Server to interact with live Bitbucket data through remote MCP tools, all from the terminal.

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