Social Fetch

Documentation

REST API reference, quickstart, TypeScript SDK, MCP server and credits. Start with quickstart or the capability matrix.

Social Fetch is a REST API for normalized social media data. Look up profiles, posts, and engagement metrics across Instagram, TikTok, X/Twitter, YouTube, and more — one JSON shape, one API key.

Start with your AI tool

Paste this prompt into Cursor, Claude Code, or any AI IDE. It will read the docs and integrate Social Fetch for you.

The essentials

Pick your path

Quickstart

Make your first authenticated request and learn the response envelope in a few minutes.

Recipes

Copyable workflows — brand monitoring, transcripts, ads, creator scoring, Reddit research.

TypeScript SDK

Typed client methods and Result-based error handling instead of raw HTTP.

API reference

Every operation, with parameters, examples, and response schemas.

Credits & billing

Which routes cost credits, how to read creditsCharged, and what 402 means.

Integrations

SDK, MCP, n8n, Apify, x402 — connect Social Fetch to your stack.

Not sure where to begin? Match your setup:

• Calling the API directly — Quickstart → Errors → Credits → API reference.
• Building in TypeScript — Quickstart → SDK guide.
• Handing this to a coding agent — connect MCP, or point it at /llms.txt, /agents.txt, /llms.json, and /openapi.json.

Platform coverage

Every platform returns the same { data, meta } envelope.

• Instagram — profiles, posts, reels, highlights, search
• TikTok — profiles, videos, products, user search
• X/Twitter — profiles, tweets, communities, search
• YouTube — channels, videos, transcripts, playlists, search
• Yelp — paginated business reviews returned directly by the API (source availability varies by review category)
• Facebook, Reddit, LinkedIn, Pinterest, Threads, Bluesky, Twitch, GitHub, Rumble, Spotify, Apple Music, SoundCloud, Telegram, Linktree, Hacker News, Truth Social, Google, Amazon — profiles, posts, and platform-specific lookups
• Web — fetch any page as Markdown or HTML, or ask a question about it
• Monitors & webhooks — schedule recurring checks and receive signed deliveries
• Utilities — whoami, balance, and health

See the API reference for every operation and its schema.

Docs for machines

Building with a coding agent or generating client code:

• Append .mdx to any docs URL for the raw Markdown, e.g. /docs/quickstart.mdx.
• /llms.txt — curated discovery index: coverage, why to use it, workflow-oriented doc links (~100 lines).
• /agents.txt — agent onboarding, auth/pagination rules, and crawl allowlist.
• /llms-endpoints.txt — every operation with a link to that route's markdown page.
• /llms-{platform}.txt — per-platform files with parameters, credits, and example curls (from OpenAPI).
• /llms.json — structured route inventory with parameters, pagination, outcomes, credits, and SDK mappings.
• /openapi.json — full schema for codegen, validation, and tooling.
• Capability matrix — every operation in one generated table: identifiers, pagination, outcomes, credits, and SDK method. Prefer /llms.json for agents.

[

Create an API key, call whoami, and read the `{ data, meta }` envelope. Copy-paste curl included.

](https://www.socialfetch.dev/docs/quickstart)