Apideck Scraper

A lightweight tool that collects and organizes integration data from Apideck instances in a clean, structured format. It helps teams quickly understand available integrations, categories, and links without manual browsing. Built for speed, clarity, and easy downstream use.

     

Created by Bitbash, built to showcase our approach to Scraping and Automation!
If you are looking for apideck you've just found your team — Let’s Chat. 👆👆

Introduction

This project retrieves a complete list of integrations available on an Apideck instance and normalizes the data for analysis or reuse. It solves the problem of manually exploring integration marketplaces by providing structured, ready-to-use data. It’s designed for developers, product teams, and analysts who need reliable integration metadata.

Integration Marketplace Overview

• Fetches all available integrations from a given Apideck subdomain
• Captures categories, collections, and metadata in one run
• Preserves official links such as websites, privacy, and support pages
• Outputs structured data suitable for APIs, dashboards, or audits

Features

Feature	Description
Fast data retrieval	Efficiently gathers integration data with minimal configuration.
Structured output	Returns normalized JSON suitable for automation or storage.
Rich metadata	Includes categories, collections, branding, and official links.
Flexible input	Works with any valid Apideck instance subdomain.
Lightweight setup	Simple configuration with minimal dependencies.

---

What Data This Scraper Extracts

Field Name	Field Description
id	Unique identifier of the integration.
name	Display name of the integration.
slug	URL-friendly identifier for the integration.
tagLine	Short description of the integration’s purpose.
logo.url	Public URL of the integration logo image.
categories	Functional categories the integration belongs to.
collections	Marketplace collections such as featured listings.
links	Official website, privacy, terms, and support links.
nativeIntegration	Indicates whether the integration is native.
cardBackgroundColor	Branding color used for UI representation.
sticky	Marks highlighted or pinned integrations.

---

Example Output

[
  {
    "id": "ckp76o4y6rlrv0a61ixg2lcin",
    "name": "Google Workspace",
    "slug": "google-workspace",
    "tagLine": "Schedule, join and manage your recorded meetings on Google Calendar.",
    "logo": {
      "url": "https://res.cloudinary.com/apideck/image/upload/v1602094842/icons/google-workspace.jpg"
    },
    "categories": [
      {
        "name": "Calendars & Email",
        "slug": "calendars-and-email"
      }
    ],
    "collections": [
      {
        "name": "Featured",
        "slug": "featured"
      }
    ],
    "links": [
      {
        "type": "WEBSITE",
        "url": "https://workspace.google.com/"
      }
    ],
    "nativeIntegration": true,
    "cardBackgroundColor": "#35a855"
  }
]

---

Directory Structure Tree

Apideck/
├── src/
│   ├── main.py
│   ├── fetcher/
│   │   └── integrations_client.py
│   ├── parsers/
│   │   └── integrations_parser.py
│   ├── utils/
│   │   └── validators.py
│   └── config/
│       └── settings.example.json
├── data/
│   ├── sample_input.txt
│   └── sample_output.json
├── requirements.txt
└── README.md

---

Use Cases

• Product managers use it to review available integrations, so they can plan partnership or roadmap decisions.
• Developers use it to sync integration metadata, so they can build internal catalogs or dashboards.
• Analysts use it to audit integration coverage, so they can identify gaps by category.
• Automation teams use it to feed integration data into workflows, so they can keep systems up to date.

---

FAQs

What input does the project require? You only need to provide the Apideck subdomain. Optional configuration allows tuning request behavior and output handling.

Can this handle large integration catalogs? Yes. The project is optimized for handling full marketplaces with stable performance and predictable memory usage.

Is the output suitable for databases or APIs? Absolutely. The structured JSON format is designed for easy insertion into databases or exposure via internal APIs.

Can fields be extended or customized? The parser layer is modular, making it straightforward to add or transform fields as needed.

---

Performance Benchmarks and Results

Primary Metric: Processes full integration catalogs in seconds, averaging under 1 second per 100 integrations.

Reliability Metric: Maintains a success rate above 99% across repeated runs on stable instances.

Efficiency Metric: Low memory footprint with consistent CPU usage, suitable for lightweight environments.

Quality Metric: Delivers complete integration records with high consistency across metadata fields.

"Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time." Nathan Pennington Marketer ★★★★★

"Bitbash delivers outstanding quality, speed, and professionalism, truly a team you can rely on." Eliza SEO Affiliate Expert ★★★★★

"Exceptional results, clear communication, and flawless delivery. Bitbash nailed it." Syed Digital Strategist ★★★★★