Circleci

CircleCI is a continuous integration and delivery platform that automates your build, test, and deployment pipelines. It helps engineering teams ship code faster by running automated workflows whenever changes are pushed to a repository.

Connecting CircleCI to Coupler.io lets you pull pipeline, workflow, and job data into your destination of choice — whether that's a spreadsheet, a BI tool, or an AI assistant.

Why connect CircleCI to Coupler.io?

• Track CI/CD health over time — export pipeline and job execution data to monitor build success rates, failure trends, and deployment frequency

• Analyze performance metrics — use Insights data to identify slow workflows, flaky jobs, and branches causing the most failures

• Combine with other sources — join CircleCI data with GitHub, Jira, or project management tools to get a full picture of your engineering delivery

• Send data to AI tools — pipe metrics into ChatGPT, Claude, Gemini, or other AI destinations to generate automated reports or spot anomalies

Prerequisites

• A CircleCI account (Free, Performance, or Scale plan)

• A CircleCI personal API token — generate one at User Settings → Personal API Tokens

• Your organization slug and project IDs (available in CircleCI project settings URLs)

Quick start

Start with the Pipelines or Insights metrics entity — these give you the broadest view of CI/CD activity right away.

How to connect

1

Create a new data flow. In Coupler.io, click Add data flow and search for CircleCI as your source.

2

Authenticate with your API key. Paste your CircleCI personal API token into the API key field. You can generate a token at CircleCI → User Settings → Personal API Tokens.

3

Select an entity. Choose what data you want to pull — for example, Pipelines, Workflows, Jobs, or Insights metrics. See the table below for a full list of available entities.

4

Set a start date. Use the date picker to define how far back you want data to go. This controls the earliest records included in your export.

5

Choose a destination. Select where your data should land — Google Sheets, Excel, BigQuery, Looker Studio, or an AI destination like ChatGPT, Claude, or Gemini.

6

Run the data flow. Click Run to execute a manual sync and verify your data loads correctly.

Available entities

Entity	Description
Pipelines	Pipeline execution records and metadata
Workflows	Workflow definitions and execution data
Jobs	Individual job executions within workflows
Workflow jobs	Jobs associated with specific workflows
Insights metrics	Performance metrics and analytics for projects
Insights branches	Branch-level insights and statistics
Projects	All projects accessible to the authenticated user
Specific projects	Detailed information about a specific project
Contexts	Environment variables and secrets stored in contexts
Self IDs	User identification for the authenticated user
Self collaborations	Collaboration details and permissions
Mes	Profile and analytics data for the authenticated user