1. Manual ways to connect Google Sheets and Jira

If you’re just getting started, you can stitch Google Sheets and Jira together with a few straightforward, hands-on methods. They’re not glamorous, but they’re familiar and help you understand the data you actually need.

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Method 1: Export Jira issues as CSV, then import to Sheets

1. In Jira, go to Filters → View all issues and build your search or JQL query.
2. When the list looks right, click Export in the top-right of the issue list.
3. Choose Export to CSV (all fields) or Export to CSV (current fields).
4. Save the CSV file to your computer.
5. Open Google Sheets and go to File → Import → Upload.
6. Select your CSV file and choose Insert new sheet(s).
7. Clean up columns, apply filters, and build charts as needed.

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Pros: Simple, no extra tools, works in any Jira plan.
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Cons: Data goes stale immediately; you repeat this process every time you need an update.

Official docs: Jira exporting options – https://support.atlassian.com/jira-cloud-administration/docs/export-issues/ ; Google Sheets import – https://support.google.com/docs/answer/40608

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Method 2: Copy/paste from Jira search into Sheets

1. In Jira, open your issue search with the fields you care about (e.g., Key, Summary, Status, Assignee, Story Points).
2. Press Ctrl+A / Cmd+A in the issue table (not the whole page) to select rows.
3. Press Ctrl+C / Cmd+C to copy.
4. Open Google Sheets and select the top-left cell where you want data.
5. Press Ctrl+V / Cmd+V to paste.
6. Use Data → Create a filter in Sheets to sort and filter.

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Pros: Fast for ad-hoc analysis; no setup.
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Cons: Easy to miss hidden columns or rows; formatting can be messy; still manual and non-repeatable.

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Method 3: Use Google Sheets formulas on static Jira data

Once your Jira data is in Sheets (via CSV or copy/paste), you can:

• Build pivot tables (Data → Pivot table) to see status counts or assignee workloads.
• Use formulas like =COUNTIF(), =SUMIF(), and =FILTER() to track SLA breaches, overdue issues, or story points per team.
• Create charts and dashboards and share them via File → Share.

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Pros: Powerful for reporting once data is there.
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Cons: Still depends on manual refreshes; formulas break when columns change.

Official Google Sheets help – https://support.google.com/docs

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2. No-code integration with official add-ons and automation tools

Manual exports won’t scale for a growing business, agency, or sales team. That’s where no-code tools step in.

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Method 4: Jira Cloud for Sheets (Atlassian’s official add-on)

This free add-on pulls Jira Cloud issues directly into Google Sheets and lets you query with JQL.

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Setup:

1. Install Jira Cloud for Sheets from the Google Workspace Marketplace: https://workspace.google.com/marketplace/app/jira_cloud_for_sheets/1065669263016
2. Open a Google Sheet and go to Extensions → Jira Cloud for Sheets → Open.
3. Authenticate with your Jira Cloud account.

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Importing Jira issues:

1. In the sidebar, choose Basic or Advanced mode.
2. Use Basic to select a Jira site, project, and filter.
3. Use Advanced to write a custom JQL query (e.g., project = MKT AND statusCategory != Done ORDER BY created DESC).
4. Choose which fields to return and click Get data.
5. Set a refresh schedule (e.g., every hour) so the sheet stays up to date.

You can also use the custom function =JIRA("your JQL here") directly in a cell.

Official docs – https://confluence.atlassian.com/jirasoftwarecloud/jira-cloud-for-sheets-966051683.html

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Pros: Free, supported by Atlassian, JQL-powered, scheduled refresh.
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Cons: Primarily one-way (Jira → Sheets); complex workflows still need more tooling.

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Method 5: Google Sheets Integration by Mobility Stream (advanced, bi-directional)

If you need real-time, bi-directional sync and admin controls, Mobility Stream’s Google Sheets Integration is built for that.

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Key capabilities (from Atlassian Marketplace):

• Export Jira issues (and related data like Assets, Changelogs, Worklogs) to Sheets.
• Automatically update Sheets whenever a Jira issue changes.
• Make edits in Sheets and sync them back to Jira using their free Sheets add-on.
• Configure exports, permissions, and audit logs directly in Jira.

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Setup:

1. Install the app from Atlassian Marketplace – https://marketplace.atlassian.com/apps/1216313/google-sheets-integration
2. Configure an export inside Jira (choose projects, fields, and schedule).
3. Open the corresponding Google Sheet and install the free add-on they provide – https://workspace.google.com/marketplace/app/integration_for_jira_by_mobility_stream/331237863609

Docs – https://docs.mobilitystream.com/gsi/

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Pros: Real-time sync, bi-directional updates, admin controls, works with Jira Cloud and Data Center.
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Cons: Paid app; more configuration overhead.

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Method 6: Zapier for event-based automation

Zapier connects Google Sheets and Jira Software Cloud via no-code Zaps.

Common templates – https://zapier.com/apps/google-sheets/integrations/jira-software-cloud

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Examples:

• Create Jira issues from new Google Sheets rows.
• Log new Jira issues into a Google Sheet (via JQL).
• Update Jira issues when a row is edited in Sheets.

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Basic setup for “Create Jira issues from new Sheets rows”:

1. In Zapier, click Create Zap.
2. Trigger: Google Sheets → New Spreadsheet Row (choose spreadsheet and worksheet).
3. Action: Jira Software Cloud → Create Issue.
4. Map columns (e.g., Summary, Description, Issue Type, Assignee, Labels) to Jira fields.
5. Test the Zap and turn it on.

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Pros: Great for conditional, event-based workflows; many templates; no coding.
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Cons: Per-Zap limits and pricing; doesn’t handle complex, multi-step desktop workflows.

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3. Scaling with AI computer agents (Simular-style automation)

No-code tools handle APIs well, but your work isn’t only APIs. You and your team still:

• Log into Jira and Google accounts.
• Open specific dashboards and Sheets.
• Click through filters, tweak JQL, format tables.
• Download or attach files, send links to stakeholders.

This is exactly where an AI computer agent platform like Simular Pro shines: it operates your desktop, browser, and cloud apps the way a human would—just faster and more reliably.

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Method 7: AI agent as your reporting ops assistant

Imagine you want a daily executive dashboard pulling from Jira into Google Sheets.

You can train a Simular Pro agent to:

1. Open your browser, log into Jira Cloud.
2. Navigate to the right project and saved filter or construct a JQL search.
3. Open Google Sheets, locate the reporting workbook, and select the correct tab.
4. Use the Jira Cloud for Sheets sidebar to refresh queries or re-run JQL.
5. Reformat columns, update pivot tables, and refresh charts.
6. Publish the report (e.g., copy chart images or links into an email or Slack).

Because Simular Pro is built for production-grade reliability and thousands to millions of steps, you can schedule this agent to run daily, or trigger it via a webhook from your CRM or analytics stack.

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Pros:

• No need to wire APIs; the agent operates the real UI.
• Works across Jira, Google Sheets, email, Slack, and more in one flow.
• Transparent execution: every step is readable, inspectable, and tweakable.

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Cons:

• Requires an initial "onboarding" run where you show the agent what “good” looks like.
• Best suited for teams that care about repeatable, high-volume workflows.

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Method 8: AI agent to bridge business users and Jira

Sales and marketing teams often live in their own spreadsheets and resist jumping into Jira. An AI computer agent can:

1. Watch a lead or campaign tracker in Google Sheets.
2. When new rows are added or status changes, open Jira and create or update issues.
3. Add context from CRM, docs, or emails by browsing the web or your other tools.
4. Update the Google Sheet with Jira issue keys, status, and assignees.

Instead of asking non-technical teammates to learn Jira, they keep using Sheets. The agent quietly keeps both systems synchronized, acting like a digital project coordinator.

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Pros:

• Reduces friction for non-Jira users.
• Handles messy, real-world flows (different tabs, inconsistent data) better than brittle scripts.

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Cons:

• You should design clear rules (e.g., how to map Sheet rows to Jira projects and issue types).

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Method 9: End-to-end workflows across desktop, browser, and cloud

Simular’s neuro-symbolic agents combine LLM flexibility with symbolic precision. That means your agent can:

• Read a campaign brief in Google Docs.
• Create a plan in Sheets.
• Open Jira, spin up epics and tasks from the plan.
• Monitor progress and update Sheets dashboards for leadership.

All of this happens as a single, inspectable workflow—no patchwork of Zaps and scripts.

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Pros:

• True "delegate the whole process" capability.
• Scales beyond just Google Sheets and Jira into the rest of your toolchain.

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Cons:

• Requires thinking in workflows, not single tasks—but once defined, it runs like an extra team member.

Official Simular Pro overview – https://www.simular.ai/simular-pro

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