# Applora - Shopify App Store Intelligence (`scoutlayer/applora`) Actor Applora tracks every app, category, keyword, review, and ranking on the Shopify App Store daily and serves it live over MCP. - **URL**: https://apify.com/scoutlayer/applora.md - **Developed by:** [Scoutlayer](https://apify.com/scoutlayer) (community) - **Categories:** AI, Agents, E-commerce - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. - **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use). - **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`. - **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`. - **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`. - **Any other language** — the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README [Applora](https://applora.ai) is a market intelligence platform for the Shopify App Store. It crawls every app, category, keyword, review, and ranking on the store daily and turns that raw data into a structured dataset you can browse in a dashboard or query live from an AI agent over MCP. Built for Shopify app developers who want to validate a new app idea, find keyword and category whitespace, track competitors, or mine reviews for feature ideas — grounded in real, current data instead of guesswork. ![Applora — Shopify App Store Intelligence](https://applora.ai/og.png) ### What Applora tracks Applora runs its own crawlers against the Shopify App Store around the clock and keeps the following up to date: | Data | What's in it | | --------------- | ---------------------------------------------------------------------------------------------------------------------------------------------- | | **Apps** | Name, description, pricing tiers, rating, review count, Built for Shopify status, developer, category and keyword rankings, daily rank history | | **Categories** | Every App Store category — app count, average rating, review growth, top-ranked apps with 30-day position trends | | **Keywords** | App Store search terms — how many apps compete for each, who ranks, and how rankings move over time | | **Reviews** | Verbatim, reviewer-written text (not an AI summary) — filterable by rating, searchable per app | | **Merchants** | Shopify merchants surfaced from public App Store reviews, plus which apps they've installed | | **Rising apps** | New apps (by launch date) climbing rankings fastest in a category or keyword, over 7/30/90-day windows | That data powers the [Applora dashboard](https://applora.ai) — filterable app search, category and keyword opportunity finders, review breakdowns, and a rising-apps leaderboard — as well as the MCP server described below. ### Connect over MCP Applora exposes the same data as a set of [MCP](https://modelcontextprotocol.io) tools, so an AI agent (Claude, ChatGPT, Cursor, or your own) can query it directly instead of you copy-pasting App Store pages into a prompt. Add this to your MCP client's config: ```json { "mcpServers": { "applora": { "type": "http", "url": "https://applora.ai/mcp" } } } ``` The first connection walks you through a standard OAuth flow (Dynamic Client Registration + an in-browser consent screen) — no API key to copy around. Once connected, an agent gets tools like: | Tool | What it does | | ------------------------------------------ | --------------------------------------------------------------------------------------- | | `search_apps` | Search/filter apps by name, category, pricing, Built for Shopify status, rating | | `get_app` | Full profile for one app — rating, pricing, rankings, review trend, rating distribution | | `list_categories` / `get_category_ranking` | Every category, or ranking detail + top apps for one | | `search_keywords` / `get_keyword_ranking` | Keyword competition search, or ranking detail + top apps for one | | `get_app_reviews` | Paginated, verbatim reviews for an app | | `search_merchants` / `get_merchant` | Merchant search, or one merchant's profile + installed apps | See the [MCP setup guide](https://applora.ai/mcp-server) for connecting Claude Code, Claude Desktop, ChatGPT, Cursor, or a generic `.mcp.json`, and the [`agent-skills`](https://github.com/applora/agent-skills) repo for a ready-made Shopify App Store market-research skill that teaches an agent how to use these tools well (competitor teardowns, keyword opportunity finding, category whitespace, merchant complaint mining). ### What you can use it for - **Validating a new app idea** — find underserved categories and keyword gaps before writing a line of code. - **Growing an app you've already shipped** — track competitors, keyword rankings, and review sentiment to prioritize your next release. - **Managing more than one app** — keep every app, category, and keyword you care about in one place, or let your agent pull it on demand over MCP. - **Mining competitor reviews** — see what merchants love, complain about, and request in apps you compete with, without reading hundreds of reviews by hand. ### Get started - [Sign up](https://applora.ai/sign-up) — free tier included, no credit card required. - [Pricing](https://applora.ai/pricing) — Pro unlocks unlimited access, CSV export, and MCP server access. - [Browse the App Store dataset](https://applora.ai/apps) without an account. # Actor input Schema ## `note` (type: `string`): Optional free-text note, echoed back in the output. This Actor is a placeholder page only — Applora's live Shopify App Store data is served over MCP, not through Apify. See the README for the MCP connection details. ## Actor input object example ```json {} ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("scoutlayer/applora").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("scoutlayer/applora").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call scoutlayer/applora --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scoutlayer/applora", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/acts/iWY2FvUQomrWKNUaL/builds/TlgOI3XTQfzEx4lsx/openapi.json