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Social Fetch is the social media data API for teams that need to ship features, not maintain scrapers.
Every major platform changes its DOM, blocks proxies, and breaks homegrown integrations. Social Fetch handles that infrastructure โ headless browsers, rate limits, normalization โ so you get clean, live JSON back on every request. No stale cache. No per-platform parsers in your codebase.
What you can fetch: profiles and follower data, posts and reels, comments and threads, video transcripts, hashtag/keyword search, ad library intelligence, and engagement metrics โ across TikTok, Instagram, YouTube, X, LinkedIn, Facebook, Reddit, Threads, GitHub, Spotify, and more.
Built for: creator tools, marketing analytics, brand safety and impersonation detection, competitive intelligence, enrichment pipelines, monitoring dashboards, and AI agent workflows. Integrate with cURL, Python, Node, our official TypeScript SDK, or our MCP server for Cursor and Claude.
Pricing: pay-as-you-go credits that never expire. No monthly subscription. Start with 100 free credits โ no credit card required.
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SocialFetch.dev's answer
Social Fetch provides a unified REST API that lets developers collect public data from 20+ social platforms โ TikTok, Instagram, YouTube, X, LinkedIn, Reddit, Facebook, Threads, and more โ using a single consistent JSON schema. There is no need to learn or maintain separate APIs for each network. Credits never expire, and you only pay for what you use, making it ideal for both prototyping and production-scale data pipelines.
SocialFetch.dev's answer
Unlike solutions that require you to set up and maintain separate API integrations for each platform, Social Fetch gives you one API key and one consistent schema across all supported networks. You get the same response structure whether you are fetching TikTok videos, Instagram posts, or YouTube channels. The pay-as-you-go model means no wasted monthly spend on idle subscriptions, and credits never expire so there is no pressure to use them up.
SocialFetch.dev's answer
Social Fetch is primarily used by developers, data engineers, and growth marketers who need programmatic access to social media data without building and maintaining individual platform integrations. Common use cases include social analytics tools, influencer research platforms, content aggregation pipelines, brand monitoring dashboards, and AI training datasets that require large-scale social content.
SocialFetch.dev's answer
Social Fetch was founded by Luke Askew, a developer who repeatedly ran into the same problem while building social analytics tools: every platform had a different API, different authentication flows, different rate limits, and different response shapes. Building and maintaining integrations for even a handful of platforms was a significant ongoing burden. Social Fetch was created to solve this by acting as a single abstraction layer, so developers can focus on what they are building rather than on the plumbing beneath it.
SocialFetch.dev's answer
Social Fetch is built on Next.js and TypeScript, deployed on Vercel. The API layer is serverless and runs on edge infrastructure for low latency globally. Data is processed and stored using cloud-native services, and the platform uses tRPC for type-safe internal APIs. The codebase is a TypeScript monorepo, enabling shared types between the API, frontend, and internal tooling.
SocialFetch.dev's answer
Social Fetch is currently used by early-stage startups, independent developers, and small analytics teams. As a newer product launched in 2024, we are still growing our customer base. If you are interested in using Social Fetch or would like to be featured here, please reach out at hello@socialfetch.dev.
Based on our record, Roboflow seems to be more popular. It has been mentiond 38 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.
Computer vision is transforming industries by automating decision making based on visual data. From facial recognition to autonomous driving, the need for efficient computer vision solutions is growing rapidly. This article explores how Roboflow combined with ReductStore, a time-series object store optimized for managing continuous data streams, can improve computer vision applications. ReductStore is designed... - Source: dev.to / almost 2 years ago
Roboflow is the fastest way to use computer vision in production. We help developers give their software the sense of sight. Our end-to-end platform[1] provides tooling for image collection, annotation, dataset exploration and curation, training, and deployment. Over 250k engineers (including engineers from 2/3 Fortune 100 companies) build with Roboflow. We now host the largest collection of open source computer... - Source: Hacker News / over 2 years ago
Roboflow - create and deploy a custom computer vision model with no prior machine learning experience required. The free tier includes up to 1,000 free source images. - Source: dev.to / over 2 years ago
Roboflow | Open Source Software Engineer, Web Designer / Developer, and more. | Full-time (Remote, SF, NYC) | https://roboflow.com/careers?ref=whoishiring0224 [2]: https://roboflow.com/universe?ref=whoishiring0224 [4]: https://github.com/roboflow/supervision [6]: https://www.youtube.com/@Roboflow. - Source: Hacker News / over 2 years ago
The annotations will be completed on the [Roboflow](https://roboflow.com) platform. The compensation for this project is $0.40 per image, totaling $200 for the completion of all 900 images. Source: about 3 years ago
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