Every social platform.
One structured API.

FetchLayer is a structured social data API for developers and AI agents. It provides public discussions, app and business reviews, ad libraries, maker communities and storefront catalogues as clean JSON through REST and MCP, so you get consistent fields back regardless of which platform you are pulling from. There is no scraper code to write or maintain, no proxy pool to rotate, and no HTML to parse — every endpoint returns the same predictable JSON shape. The API runs at 99.5% uptime across all endpoints and never serves cached results: every call fetches live, publicly available data at the moment you request it. Authentication is a single Bearer token, and every endpoint is a POST with a JSON body, so a working request in one language ports to any other in minutes. A free tier (no credit card required) is available across every platform, and pay-as-you-go pricing starts at $1.99 per 1,000 requests once you are ready to scale past it.

There are 36 platforms live today on one account, across eight kinds of source: social (Reddit, Twitter/X, YouTube, TikTok), app stores (App Store, Google Play), ad libraries (Facebook, Google, TikTok, LinkedIn), review sites (Trustpilot, Glassdoor, Tripadvisor, Google Maps), maker communities (Product Hunt, Printables, MakerWorld), storefronts (Shopify, WooCommerce), marketplaces (Amazon, eBay, AliExpress, Temu) search engines (Bing and DuckDuckGo) and AI assistants (ChatGPT). Between them they expose 240 endpoints — posts and comment trees, app and business reviews, the ads a competitor is running with their creative files, product launches, and full store catalogues with prices and stock. Every platform uses the same Bearer token, the same request/response shape, and the same developer-first API model, so learning one endpoint means you already know how the rest work. There are no per-platform sign-ups, no separate billing relationships, and no credit multipliers: one API request equals one credit everywhere. New platforms are added to every existing account automatically as FetchLayer ships them, with the same credentials and the same bill — no upgrade step and no new integration required on your end.

FetchLayer is for developers building social listening tools, lead generation workflows, research products, monitoring systems, and AI agent integrations that need public platform data without scraper maintenance. If your product needs to read what people are saying on Reddit, track App Store or Trustpilot reviews, pull YouTube comments, watch which ads a competitor is running, or walk a storefront's catalogue for prices — and you would rather call a stable JSON API than run and babysit your own scraping infrastructure — this is built for that. It is also used as a second source behind an existing pipeline: teams route queries to FetchLayer when their primary provider rate-limits or goes down, without changing their data model. Individual developers use the free tier and pay-as-you-go pricing to prototype and ship small projects; teams running production monitoring or research pipelines typically move to a subscription plan (from $25/mo) or an Enterprise/Unlimited tier once volume becomes predictable.

Yes. FetchLayer supports direct REST access and a native Model Context Protocol (MCP) server, so tools like Cursor, Claude Desktop, Claude Code, and Windsurf can use social data through normal agent tool-calling instead of custom wrapper code. The MCP server runs at mcp.fetchlayer.dev and exposes every supported platform's tools — an agent can search Reddit, pull App Store reviews, read a company's Trustpilot rating, or walk a Shopify catalogue the same way it would call any other tool in its toolbox. Setup is a config-file change per client, not a new integration — see fetchlayer.dev/mcp for connection steps by client. Because the agent receives typed JSON rather than raw HTML, it does not burn context re-parsing pages or fail when a platform changes its markup. This is also why FetchLayer publishes machine-readable service manifests (llms.txt, an MCP server card, and per-platform agent-skill definitions) alongside its human-facing docs.