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GapQuery is an app ecosystem intelligence platform for developers and micro SaaS founders. It scans 11 major app ecosystems โ Shopify, WordPress, QuickBooks, Atlassian, Xero, Slack, Monday, GitHub, Freshworks, Zendesk, and Zoho โ covering 35,600+ apps to surface market gaps, pricing opportunities, and missing integrations. Connect GapQuery to Claude Code via MCP and use 17 AI-powered tools to discover underserved categories, spot overpriced apps, identify developer whitespace, and analyze cross-ecosystem patterns. Save opportunities to your pipeline and run deep research across market validation, competition, revenue, technical feasibility, keywords, and go-to-market strategy.
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GapQuery's answer:
GapQuery connects directly to your AI coding environment via MCP. Instead of browsing dashboards, you query 11 app ecosystems and 35,600+ apps through natural language, discovering market gaps, pricing opportunities, and missing integrations right where you code. It's market research that meets you in your terminal.
GapQuery's answer:
Most market research tools focus on consumer app stores or require expensive subscriptions. GapQuery is purpose built for B2B app ecosystems like Shopify, QuickBooks, and Atlassian, the platforms where micro SaaS businesses actually get built. It's a one time purchase starting at $29, not a recurring fee, and it integrates directly into Claude Code so insights turn into action immediately.
GapQuery's answer:
Solo developers, indie hackers, and micro SaaS founders who want to build apps for established platforms like Shopify, WordPress, or QuickBooks and want data to validate their ideas before writing code.
GapQuery's answer:
Laravel 12, Livewire 4, MySQL 8, Python (scrapers), Tailwind CSS, and Anthropic's Model Context Protocol (MCP) for AI tool integration.
GapQuery's answer:
GapQuery started as a personal tool. I was building micro SaaS apps and kept manually searching app stores to figure out what was missing. I realized the same gap analysis I was doing by hand could be automated: scrape the ecosystems, normalize the data, and let AI surface the patterns. What began as a spreadsheet became a database of 35,600+ apps across 11 ecosystems.
Based on our record, Tableau Public seems to be more popular. It has been mentiond 12 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Now, if you do want to play around with data visualizations, you can do that for free with Tableau Public https://public.tableau.com/en-us/s/. Source: about 4 years ago
Tableau Public - https://public.tableau.com/en-us/s/. Source: about 4 years ago
Tableau and PowerBI are generally viewed as industry standard tools. The good news is you have free options for both! Tableau Public and PowerBI Desktop are what you're looking for. Try them out and pick which one you like more. The skills are pretty transferable once you master the basics. As far as python ML tools, ones that pop up pretty frequently are scikit-learn (questionable math notwithstanding), XGBoost,... Source: over 4 years ago
I played with the idea of doing something similar and putting it all in Google Sheets (https://www.google.com/sheets/about/) so I could visualize it all in Tableau Public (https://public.tableau.com/en-us/s/). Source: over 4 years ago
I record everything in a spreadsheet and then built a set of dashboards using Tableau. Took a bit to get set up, but once I had it, I can produce the summary in a few minutes. Here's an example of my weekly summary. If you're interested, happy to send you the Tableau workbook so you can take a look. Source: over 4 years ago
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