How to Query Live Strava Data in Claude Desktop

Model Context Protocol (MCP) is an emerging, open-source standard for connecting LLMs with external services and data sources. Through MCP Servers, AI clients can perform actions like opening Jira tickets, posting Slack messages, committing GitHub branches and more. With CData MCP Server, these capabilities expand exponentially.

CData MCP Server provides schema-aware context to AI tools — whether you're using it for AI-assisted code generation in IDEs like Cursor, or for querying live data through chat interfaces like Claude Desktop.

In this article, we guide the reader through installing CData API Driver for MCP Server, configuring the connection to Strava, and asking questions of the data in Claude Desktop.

Prerequisites

You need to download Claude Desktop (download) and create an account before continuing.

Overview

Here's a quick overview of the steps:

1. Download and install the CData API Driver for MCP Server
2. Configure the connection to Strava
3. Ask questions about the data in Claude Desktop

Step 1: Download and install CData MCP Server

1. To begin, navigate to https://www.cdata.com/solutions/codeassist/ and download the CData API Driver for MCP Server. 👁 Downloading the CData MCP Server installer
   
2. Find and double-click the installer to begin the installation. 👁 Running the installer for CData MCP Server (Google Sheets is shown.)
   
3. Follow the prompts to complete the installation. 👁 Completing the CData MCP Server installation (Google Sheets is shown).
   

When the installation is complete, you are ready to configure MCP Server by connecting to Strava.

Step 2: Configure the connection to Strava

1. After installation, the MCP Server configuration wizard should open automatically. 👁 The MCP Server configuration wizard.
   

   NOTE: If the wizard does not open automatically, search for "CData MCP Server" in the Windows search bar and double-click the application. 👁 Opening the MCP Server configuration wizard (Google Sheets is shown).
   

2. Click the dropdown menu in MCP Configuration > Configuration Name and select "
3. Name the configuration (e.g. "cdataapi") and click "OK."

   NOTE: This name is used as the name for the MCP server and as the prefix for all of the MCP Server's tools.

   👁 Naming the configuration.
   

4. Connecting to Strava

   To authenticate to Strava, and connect to your own data or to allow other users to connect to their data, you can use the OAuth standard.

   Using OAuth Authentication

   You must create a custom OAuth application to connect to Strava. To create a custom OAuth application:

   1. Log into the Strava API Settings page
   2. Create a new application or select an existing application
   3. Set the "Authorization Callback Domain" to your callback URL domain (e.g. localhost)
   4. Note down the Client ID and Client Secret

   After setting the following connection properties, you are ready to connect:

   • AuthScheme: Set this to OAuth.
   • InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to manage the process to obtain the OAuthAccessToken.
   • OAuthClientId: Set this to the Client ID from your Strava API application.
   • OAuthClientSecret: Set this to the Client Secret from your Strava API application.
   • CallbackURL: Set this to the redirect URI matching your application's callback domain.

   Example connection string:

   Profile=C:\profiles\Strava.apip;AuthScheme=OAuth;InitiateOAuth=GETANDREFRESH;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackURL=http://localhost:33333;
   

   Enter the appropriate connection properties in the configuration wizard.

   👁 Configuring the Server to connect with a specific Spreadsheet.
   
5. Click "Connect" to authenticate with Strava through OAuth. 👁 Authenticating with Google
   

   NOTE: The configuration wizard should open your browser and ask you to sign into Strava. If your browser does not open, close the configuration wizard and re-open the application using "Run as Administrator" (see below).

   👁 Running the configuration wizard with elevated permissions.
   
6. Finally, click "Save Configuration" to save the configuration. 👁 Saving the MCP Server configuration.
   

   NOTE: This saves the configuration details to a separate file and updates the Claude Desktop configuration file (claude_desktop_config.json) to start MCP Server when the Claude Desktop client starts.

With MCP Server configured, you are ready to start asking questions of your live data from Claude.

Step 3: Ask AI for answers from live Strava data

Now that we have installed MCP Server and configured a connection, we are ready to start with Strava data in Claude Desktop.

1. Open Claude Desktop. It may take a moment for MCP Server to start, but you will see the list of servers and tools available in the Claude interface (look for the settings icon below the prompt bar). 👁 The MCP servers menu showing available connections in Claude Desktop
   

   You can individually enable and disable specific tools by clicking on the server name. 👁 The expanded tool list for MCP Server in Claude Desktop
   

2. Now that you have connected, you can ask Claude questions about the Strava data. For example: "Can you give me a quantitative analysis about my closed-won opportunities by industry?"

   NOTE: Claude may need to explore the Strava data to make sense of it before it can begin answering questions of the data. The tabular model presented by CData alongside the database tools available simplify the data exploration and analysis for an LLM.

   👁 Claude Desktop displaying a quantitative analysis of live data
   

Build with MCP Server. Deploy with CData Drivers.

Download CData API Driver for MCP Server for free and give your AI tools schema-aware access to live Strava data during development. When you're ready to move to production, CData API Drivers deliver the same SQL-based access with enterprise-grade performance, security, and reliability.

Visit the CData Community to share insights, ask questions, and explore what's possible with MCP-powered AI workflows.