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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, Atlan seems to be more popular. It has been mentiond 2 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.
After evaluating few solutions in the market: We were in the market to hunt for a solution which will cost under 10k (yearly) considering the cost of opensource will be similar considering DE resource and maintenance cost etc 1. MonteCarlo - Super duper expensive - Unable to hosting in Google Cloud 2. BigEye - Good features 3. Metaplane - Overall good package but when compared to catalog and other features it... Source: over 3 years ago
I've previously built data lakes on AWS with Glue and you get the data catalog for free but it isn't convenient to explore. Enterprise-grade data catalogs such as Alation are full featured and really decent but come at a higher cost. If your preference is open source, check out Atlan and Amundsen. Source: over 3 years ago
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