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RepDB
RepDB is a one-time-purchase exercise dataset with animations for developers building fitness and workout apps — not a subscription, not a rate-limited API. You download the data once and own it: JSON (and SQLite on the higher tier), WebP images, and full EN/DE/ES translations, with no per-request billing and no dependency on our servers staying up.
A free tier includes 600+ exercises with flat-style 512×512 images, attribution-licensed for commercial in-app use. The Starter tier ($299) adds the full catalog in classic white-background style. Standard ($499) adds transparent 1024px images, looping animations, exercise relations (similar/progressions/regressions), workout templates, and embeddings — exclusive to that tier.
Every exercise includes muscle-group highlighting, equipment/muscle icons, MET values, and safety/goal tags. Compared to GIF- or JPG-based competitor APIs, RepDB images are transparent WebP with no watermarks, so they drop into any app UI without a white box around them.
Medium RepDBMedium is recommended for avid readers seeking a variety of topics ranging from personal development to technology. It's also ideal for writers looking to publish their work to a broad audience and potentially earn revenue through the platform's Partner Program.
RepDB's answer:
RepDB is sold as a one-time download, not a metered API — you own the JSON/SQLite data and WebP images outright, with no rate limits, no per-request billing, and no risk of the vendor cutting off access. It's also the only dataset in this space with EN/DE/ES translations, transparent (alpha-channel) images with no watermark, muscle-group highlighting, safety/goal tags, and looping animations on the higher tier.
RepDB's answer:
RepDB grew out of a consumer workout app its creator was building solo. Sourcing exercise images and data meant either paying for a subscription API with usage caps and no caching rights, or producing everything from scratch. The illustrated, multi-language dataset was built for us first, then split out as its own product once it became clear other indie developers had the same problem and preferred to buy the data outright rather than rent it through an API.
RepDB's answer:
Most alternatives are subscription APIs — you pay monthly, you're capped on requests, and ExerciseDB's terms of use explicitly forbid caching or storing the data at all, so every image render is a live paid API call. RepDB is the opposite: pay once, download the files, self-host with zero ongoing dependency. It's also the only option offering true DE/ES localization and transparent images instead of a white box behind every exercise.
RepDB's answer:
Solo developers and small teams building fitness or workout-tracking apps (iOS, Android, web) who need licensed exercise images and structured exercise data, but don't want to build their own media pipeline or depend on a rate-limited third-party API.
Based on our record, Medium seems to be more popular. It has been mentiond 3127 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.
I wrote a longer, feature-by-feature walkthrough of the stack on Medium if you want the deep dive on how it all wires together. Https://medium.com/@aak540114/give-your-ai-agents-a-kanban-board-not-the-keys-to-production-81ffd19370f1. - Source: dev.to / 4 days ago
FWIW, it appears that using the gh cli is much more token efficient than MCP so that's a plus. https://medium.com/@ravi.madabhushi/mcp-is-up-to-32-more-expensive-than-cli-heres-why-we-still-use-it-d18765735647. - Source: Hacker News / 5 days ago
That's the ratio the widely published numbers give [1][2]. One does not have to believe the numbers, of course, but those who do believe them are then justified to conclude that there's no moat. Which numbers you believe is of course going to affect whether you think there's a moat or not. [1] https://galileo.ai/blog/llm-model-training-cost [2]... - Source: Hacker News / 5 days ago
Kent Beck called this “test && commit || revert” in 2018, and credits Oddmund Strømme for first coming up with the idea: . - Source: Hacker News / 6 days ago
Https://medium.com/@ashishrathour1102 Looking for backend, infrastructure, platform, distributed-systems, storage-engine, or systems-programming roles. Especially interested in small/high-ownership teams working on runtimes, execution infrastructure, databases, developer infrastructure or reliability. - Source: Hacker News / 7 days ago
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