Jira issues (JQL)

Jira is a powerful project management platform used by teams to track issues, bugs, and tasks. With Coupler.io, you can pull Jira issues using JQL (Jira Query Language) filters to analyze, report on, and combine issue data with other sources.

Why connect Jira to Coupler.io?

• Flexible filtering — Use JQL to pull exactly the issues you need, whether it's a simple filter or a complex query

• Custom analysis — Export issue data to Google Sheets, Excel, BigQuery, or AI destinations like Claude or ChatGPT for advanced analysis

• Combine data sources — Join Jira issues with data from other tools (e.g., append time-tracking data, join with customer feedback)

• Automated reporting — Build dashboards in Looker Studio or other BI tools using fresh Jira data

Prerequisites

• A Jira Cloud account with at least read access to the projects you want to query

• Permission to create API tokens (if using API key authentication)

• A destination to send your data (Google Sheets, Excel, BigQuery, Looker Studio, or an AI destination)

Quick start

If you're new to JQL, start with a simple query like project = "YOUR_PROJECT_KEY" to pull all issues from a project. You can always refine the query later.

How to connect

1

Click "+ New data flow" on the Coupler.io dashboard and search for "Jira issues (JQL)".

2

Click "Authorize" in the Jira authentication modal. You'll be redirected to Jira Cloud to sign in. Coupler.io will request permission to read issues from your Jira account.

3

Select your Jira Cloud site from the "Site" dropdown. If you manage multiple Jira instances, choose the one containing the issues you want to export.

4

Enter your JQL query in the "JQL" field. For example:

• project = "PROJ" AND status = "In Progress" — all in-progress issues in a project

• assignee = currentUser() — issues assigned to you

• created >= -7d AND type = "Bug" — bugs created in the last 7 days

Leave this field empty to pull all issues accessible to you.

5

Choose an export format:

• Jira CSV export — Data in Jira's standard format (simpler, familiar layout)

• Detailed data — All metadata including IDs, URLs, and custom fields as separate columns (better for advanced analysis)

6

(Optional) Select specific columns in the "Columns" field. Enter each column name on a new line. If left empty, all navigable fields will be exported. To find column names, export a sample to a spreadsheet first and copy the headers.

7

Choose a destination for your data (Google Sheets, Excel, BigQuery, Looker Studio, Claude, ChatGPT, or another supported platform).

8

Click "Run now" to execute the data flow. After a successful manual run, you'll be able to schedule future refreshes.

What data is available?

Jira issues can include a wide range of fields depending on your Jira configuration. Common fields include:

Field	Description
Issue key	Unique identifier (e.g., PROJ-123)
Summary	Issue title or brief description
Description	Detailed issue description
Status	Current status (e.g., To Do, In Progress, Done)
Assignee	Person assigned to the issue
Reporter	Person who created the issue
Priority	Issue priority level
Type	Issue type (e.g., Bug, Task, Story)
Created	Issue creation date and time
Updated	Last update date and time
Sprint	Agile sprint (if using Scrum)
Epic	Parent epic (if using epics)
Custom fields	Any custom fields configured in your Jira instance