How to Integrate Lovable with Linear

Open your Lovable workspace and click the Settings gear icon in the top-right corner of the editor. In the Settings panel, navigate to the Connectors section and look for the 'Shared connectors' list. Scroll through the list until you find Linear — it appears alongside Slack, Stripe, Twilio, and the other 17 available connectors. Click the Linear connector card to open its configuration panel. You will see a description of what the connector provides (issue management, projects, teams, cycles) and a button to initiate the OAuth connection. Click 'Connect Linear' and a browser popup will open prompting you to sign in to your Linear account (if you are not already signed in) and authorize Lovable to access your workspace data. Once you approve the OAuth authorization, the popup closes and the connector status changes to 'Connected' with a green indicator. Lovable stores the OAuth tokens in its gateway infrastructure — you will never see a client ID, client secret, or access token anywhere in your project code. This connection is workspace-level, meaning every project under your workspace can now use Linear data. If your team has multiple Lovable workspaces, you will need to connect Linear separately in each one.

With the Linear connector active, open the chat panel in your Lovable project and describe the view you want to build. Lovable's AI now has full context about the Linear connector's capabilities — it knows the available API endpoints, data shapes (issues, projects, teams, cycles, labels, assignees), and the right code patterns to use with the gateway. Be specific about which data you want to display and how you want it organized. Mention filters like team, cycle, status, or priority if they are relevant. If you want write capabilities (creating or updating issues from the app), include that in your prompt too. The AI will generate all necessary frontend components and the server-side calls needed to interact with Linear through the gateway — no manual wiring required. After Lovable generates the initial build, check the live preview and refine with follow-up prompts. You can ask it to add filters, change the card layout, add a status badge with color coding, or include a link that opens the issue directly in Linear. The AI retains context across the conversation, so incremental refinements work well.

Read-only dashboards are useful, but many of the most powerful Linear + Lovable use cases involve writing back to Linear: a client feedback form that auto-creates an issue, an internal tool that converts meeting action items into Linear tasks, or a bug report button embedded in your product that files issues directly to the right team and cycle. In the Lovable chat, describe the write behavior you want. Be specific about which Linear fields should be populated: team, project, cycle, title, description, priority, labels, and assignee are all writable through the connector. If you want to map form inputs to Linear fields, describe that mapping explicitly — for example, 'use the dropdown to set priority' or 'auto-assign to the on-call team based on the category selected'. Lovable will generate the form component and the server-side logic to call Linear's create/update endpoints through the gateway. Because the gateway handles authentication, there is no webhook secret to configure and no Edge Function for you to write. The AI handles the integration plumbing — your job is to describe the user experience accurately so the generated code matches your intended behavior. For more complex workflows — like automatically moving an issue to a specific cycle when a status changes, or triggering a Linear issue from a Supabase database event — you can describe the full flow in one prompt and Lovable will generate both the frontend trigger and the backend logic.

The Linear MCP personal connector is separate from the shared connector and serves a completely different purpose. While the shared connector gives your deployed app runtime access to Linear data, the MCP personal connector gives Lovable's AI context about your Linear workspace while you are building — it reads your actual issues, cycle goals, and acceptance criteria so the code it generates matches your real project structure. To enable it, go to Settings → Connectors and find the 'Personal connectors (MCP)' section, which is listed separately from Shared connectors. Click on Linear in the personal connectors list and authorize access to your Linear account. This is a per-user setting, not workspace-wide — each team member configures their own personal connectors. Once connected, try starting a new feature build by referencing your Linear issues directly. You can use @Linear syntax in the Lovable chat to pull in specific issue content as context. For example, referencing an issue like ENG-142 tells the AI exactly what feature you are building, including acceptance criteria written by your product team. The AI uses this context to generate more accurate components, field names, data structures, and edge case handling — without you having to re-explain the requirements. This connector is never included in the deployed application. It is purely a development-time tool that makes the AI a better collaborator by grounding it in your actual project context.

One of the most requested Linear dashboard components for internal tools is a cycle tracker — a view that shows how a team is tracking against their current cycle goals. With the Linear shared connector, you can build this as a dedicated page or as a section within a broader engineering dashboard, and it will reflect live data from your Linear workspace whenever the page loads. A cycle tracker typically shows the current cycle name and dates, the total number of issues scoped to the cycle, a breakdown by status (Todo, In Progress, Done, Cancelled), a completion percentage, and optionally a list of unstarted issues with their assignees and priorities to surface blockers at a glance. You can also include a comparison to the previous cycle to indicate whether velocity is improving. In your Lovable chat, describe the exact metrics and layout you want. If your organization uses multiple teams, you can ask Lovable to add a team selector so the same page works across teams without rebuilding it. For teams that run multiple concurrent cycles or have custom cycle naming conventions, specify that in your prompt so the AI accounts for it in the data fetching logic. This is also a good place to use Lovable's visual editing tools (Design view) to fine-tune typography, spacing, and color after the initial build — adjusting visual styling in Design view costs no credits.