Lichess
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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, Lichess seems to be more popular. It has been mentiond 922 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.
Hi HN! I build this project to explore an idea I got in mind for a long time : Is transformer a suitable architecture for a chess bot? I built a small model (11M parameters) and trained it on human games (Elite Lichess DB). Model alone is performing around 1500 elo, but I built an harness using Monte Carlos Tree Search (MCTS) using my model heuristics to improve the model to ~2100 elo (evaluated against... - Source: Hacker News / about 2 months ago
Lichess is incredibly well optimized [0] (and an amazing public service). I'm sure that this is very cost effective for TTT, so a win-win. [0] https://lichess.org/@/revoof/blog/optimizing-the-tablebase-server/MetV0ZQd. - Source: Hacker News / 4 months ago
Https://lichess.org/@/Lichess/blog/lichess-and-take-take-take-sign-cooperation-agreement/DZS0S0Dy. - Source: Hacker News / 4 months ago
The actual blogpost: https://lichess.org/@/Lichess/blog/op1-partial-8-piece-tablebase-available/1ptPBDpC On a related note, anyone knows a Mastodon proxy that doesn't require JS and I can just pipe links through? - Source: Hacker News / 6 months ago
Lichess uses a scheme which is probably more efficient on average, described on revoof's blog[0]. Basically, it's a variable length scheme where the first 64 bits encode square occupancies, followed by piece codes (including castling, side to move, and ep with some trickery), followed by half-move clocks if necessary. 0:... - Source: Hacker News / 7 months ago
Chess.com - Play chess on Chess.com
API Direct - A pay-as-you-go social media API. Search real-time data across multiple social platforms through one standardized API. No monthly fees or commitments โ just pay per request.
Chess Tempo Database - Chess Tempo Database gives you a library of more than 2 million searchable chess games.
Apify Python SDK - Build and manage web scraping Actors in the cloud.
DecodeChess - AI chess tutor and analysis
Simple Scraper - Extract data from any website in seconds โ download instantly, scrape in the cloud, or create an API.
