Integrating Gumloop with Linear Data via CData Connect AI
Gumloop is a visual automation platform designed to create AI-powered workflows by combining triggers, AI nodes, APIs, and data connectors. By integrating Gumloop with CData Connect AI through the built-in MCP (Model Context Protocol) Server, workflows can seamlessly access and interact with live Linear data.
The platform provides a low-code environment, making it easier to orchestrate complex processes without heavy development effort. Its flexibility allows integration across multiple business applications, enabling end-to-end automation with live data.
This article outlines the steps required to configure Linear connectivity in Connect AI, register the MCP server in Gumloop, and build a workflow that queries Linear data.
Step 1: Configure Linear Connectivity for Gumloop
Connectivity to Linear from Gumloop is made possible through CData Connect AI's Remote MCP Server. To interact with Linear data from Gumloop, we start by creating and configuring a Linear connection in CData Connect AI.
- Log into Connect AI, click Sources, and then click Add Connection
- Select "Linear" from the Add Connection panel
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Enter the necessary authentication properties to connect to Linear.
You can authenticate to Linear with a personal API key or with OAuth 2.0. The API key is the simplest option for connecting with your own Linear account.
Authenticating with an API Key
Set the following connection properties:
- AuthScheme: Set this to APIKey.
- APIKey: A Linear personal API key.
To create a personal API key, log in to Linear, open Settings > Security & access > Personal API keys, select New API key, and create it. Copy the key immediately, because Linear shows it only once.
Authenticating with OAuth
OAuth requires a custom OAuth application registered in Linear (Settings > API > OAuth applications), which provides the OAuthClientId and OAuthClientSecret. Two flows are supported:
- Authorization code: Set AuthScheme to OAuth, InitiateOAuth to GETANDREFRESH, and provide OAuthClientId, OAuthClientSecret, and the CallbackURL defined in your application (e.g., http://localhost:33333). The driver opens Linear in your browser so you can grant access.
- Client credentials: Set AuthScheme to OAuthClient and provide OAuthClientId and OAuthClientSecret. This authenticates the application itself, with no browser interaction, and suits machine-to-machine integrations.
By default, the driver requests the read,write scopes. The driver refreshes the access token automatically when it expires.
- Click Save & Test
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Navigate to the Permissions tab in the Add Linear Connection page and update the User-based permissions.
Add a Personal Access Token
A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from Gumloop. It is best practice to create a separate PAT for each service to maintain granularity of access.
- Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
- On the Settings page, go to the Access Tokens section and click Create PAT.
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Give the PAT a name and click Create.
- The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.
With the Linear connection configured and a PAT generated, Gumloop is prepared to connect to Linear data through the CData MCP server.
Step 2: Connect to the MCP server in Gumloop
The MCP server endpoint and authentication values from Connect AI must be added to Gumloop credentials.
- Sign in to Gumloop and create an account
- Visit the Gumloop Credentials page to configure MCP server
- Click on Add Credentials and search and select MCP Server
- Provide the following details:
- URL: https://mcp.cloud.cdata.com/mcp
- Label: A descriptive name such as Linear-mcp-server
- Access Token / API Key: leave blank
- Additional Header: Authorization: Basic YOUR EMAIL:YOUR PAT
- Save the credentials
The MCP server is now available to build workflows in Gumloop.
Step 3: Build a workflow and explore live Linear data with Gumloop
- Visit Gumloop Personal workspace and click on the Create Flow
- Select the icon or press Ctrl + B to add a node or a subflow
- Search for Ask AI and select it
- Click Show More Options and enable the Connect MCP Server? option
- From the MCP Servers dropdown, choose the saved MCP credential
- Add a Prompt and Choose an AI Model according to your requirements
- After configuring the required details, Click Run to run the pipeline
With the workflow run completed, Gumloop demonstrates successful retrieval of Linear 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.
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