I built a social media data API to grow my own socials

Q: How much does SocialCrawl cost?

Start free with 100 credits, no credit card required. Most endpoints cost 1 credit per request. Advanced endpoints cost 5 or 10 credits. Credits never expire and there are no artificial rate limits. Paid plans scale from Starter through Growth, Pro, and Enterprise.

Hey — I'm a developer from London. I build and ship different things, small products and big ones. The last few years have taught me the same thing over and over: building is the easy part in 2026. Distribution is the whole game.

Shipping product is the one thing I'm halfway comfortable with. Telling the world about what I ship? Brutal. I kept trying to grow my social accounts the normal way and kept not growing them.

So I did what developers do when they hit a wall: I over-researched it. Roughly 500 hours of YouTube marketing content, a pile of Reddit threads, a few podcasts on loop. The conclusion was boring: every marketer who actually scales has a system they run. Not vibes, not posting whenever they felt like it — a repeatable loop.

My version of that loop: an AI that watches X, Reddit, Threads, and Instagram on a schedule, spots posts worth replying to, tracks which ones are blowing up, and drops the opportunities into my Slack every morning. Save me an hour a day. Maybe two.

I started building. Every platform had a different API. I dug through Apify, RapidAPI, and random GitHub repos looking for anything close to what I needed. The pieces existed, just scattered across a dozen providers with different auth flows, different response shapes, different pagination, different billing relationships. The fragmentation wasn't just annoying for me — it was actively making the AI worse. Claude was burning tokens re-learning every endpoint, and every new platform meant teaching it a fresh schema from scratch.

There had to be a better way.

One of my favorite tools on the internet is Firecrawl. Point it at any URL, get clean AI-ready markdown back. One API, one shape, zero parsing headaches. I kept coming back to the same question: why doesn't this exist for social media data?

So I built it. SocialCrawl, on a mission to provide the cleanest, AI-ready social media data on the internet. One API key, one response shape, 21 platforms, purpose-built agent skills and MCP servers on top. Then I rebuilt the original agent on top of the new API. The agent took a weekend. The API took the whole year.

This post is about the API — how it works, why it exists, and what you can do with it now that the hard part is done.

What is SocialCrawl?

SocialCrawl is a unified social media data API: one API key, clean structured data from 21 platforms, identical response shape every time.

That consistency is the product. 108 endpoints cover profiles, posts, comments, search, and analytics across TikTok, Instagram, YouTube, Facebook, X/Twitter, LinkedIn, Reddit, Threads, Pinterest, Twitch, and 11 more. Between them they reach over 10 billion combined monthly active users. Write one parser, handle every platform. Swap platforms later without touching your integration logic.

Why is multi-platform social data so hard to work with?

Every platform designs its API for its own ecosystem, not for anyone building across all of them.

The typical internet user actively uses 6.75 different social platforms each month, which is exactly the problem: any product that's actually useful has to cross platform boundaries, and each new platform is another integration tax. Nordic APIs put it plainly in February 2026: "In a sprawling environment, agents may struggle to find the correct endpoints or accidentally use outdated APIs, leading to task failure." Their research found that only 10-20% of APIs in a sprawled ecosystem are documented and governed well enough to be reused at all.

The social landscape today:

Dozens of official platform APIs
Each with its own auth protocol
Each with its own rate limit logic
Each with its own pagination strategy
Each with its own JSON structure
Three-to-four separate billing relationships if you want real coverage

One integration per platform if you're a developer. Custom parsing logic per source if you're an AI agent — which breaks the moment a platform ships a schema change.

SocialCrawl normalizes every response before it reaches your code.

How does a unified social media API actually work?

21 platforms. 108 endpoints. One response structure.

Whether you query TikTok, Instagram, YouTube, Reddit, or anything else, the JSON shape is identical. A post is a post. An author is an author. Metrics are metrics. Write your parser once and it handles every source.

Here's what a unified response looks like:

{
  "id": "post_abc123",
  "platform": "tiktok",
  "author": {
    "username": "creator_handle",
    "followers": 284000
  },
  "content": {
    "text": "Post caption text here",
    "media_type": "video"
  },
  "metrics": {
    "likes": 14200,
    "comments": 438,
    "shares": 892,
    "engagement_rate": 5.47,
    "estimated_reach": 312000
  },
  "meta": {
    "language": "en",
    "content_category": "tech",
    "published_at": "2026-04-14T09:22:00Z"
  }
}

The same structure comes back across every platform. Swap the platform parameter, get the same shape back.

Pagination works the same way. Every platform paginates differently behind the scenes, but SocialCrawl abstracts that into one cursor-based system. You learn the pattern once.

That's the difference between SocialCrawl and a raw social media scraping API. Scraping hands you whatever HTML or JSON the platform happened to return that week. SocialCrawl normalizes it, so a schema change upstream doesn't break your parser.

Why do AI agents need a dedicated social media API?

Because the gap between "technically scrapable" and "usable by an agent" is enormous, and nothing in the space was closing it for social data specifically.

Anthropic described the core problem in their November 2024 MCP launch: "Every new data source requires its own custom implementation, making truly connected systems difficult to scale." Adoption has moved fast since — PulseMCP listed over 5,500 MCP servers as of October 2025, with remote servers growing nearly 4x since May. None of them were for social data the way I needed it.

So SocialCrawl's MCP server is purpose-built for this one job. Not raw HTML. Not markdown from arbitrary pages. Normalized, structured social data with computed fields, ready to hand to an agent. Any MCP-compatible client (Claude Desktop, Cursor) connects with a single config block. For agent harnesses like Claude Code and Codex, the Skill installs in one command and teaches the agent every endpoint at once — so your agent doesn't burn tokens re-learning the API on every run.

The computed fields are where the real time savings land. Every response across every platform includes:

engagement_rate: likes + comments divided by followers, pre-calculated. Spot high-performing content without writing the formula yourself.
estimated_reach: audience impact derived from follower count and engagement patterns. Compare creators by influence, not raw follower counts.
content_category: AI-classified (tech, food, fashion, gaming, and more). Route posts to the right workflow automatically.
language: detected on every post. Segment multilingual data without a separate NLP step.

Other APIs hand you raw numbers. SocialCrawl calculates the metrics agents actually need, on every response, across every platform. Data arrives ready to reason on.

What can you build with it?

Short answer: anything that used to be "cool idea, but not worth the integration tax."

AI research agents and daily briefings. The original use case I built this for. An agent reads X, Reddit, TikTok, and more each morning, cross-references trends, and surfaces signals in Slack. Zero platform-specific parsing logic because the schema is the same across all of them.
Social analytics dashboards. Pull profiles, posts, and engagement metrics from 21 platforms into one data layer. One parser, every source. No per-platform maintenance when schemas change upstream.
Trend and influencer discovery. Find emerging creators, spot viral patterns, track hashtag momentum. Computed engagement_rate and content_category make cross-platform comparisons instant.
Brand and competitive monitoring. Track mentions and competitor activity across every platform simultaneously. One integration instead of twelve.

These become practical when you are not rebuilding the integration layer per platform.

See your data before writing a single line

Paste any social URL into the Explorer and see the full unified response before you write a line.

Rich result cards, sortable table view, CSV and JSON export, and a "Copy as code" button that generates the API call in your language of choice. It's the fastest way to inspect the response shape and understand what you're working with before committing to an integration.

For marketers, analysts, and researchers, the Explorer handles the whole workflow end-to-end. Paste an influencer URL, get engagement rate, follower count, content category, and post history. No API key needed.

How do you get started?

Start with 100 free credits, no credit card. Three paths from there:

API. Grab a key, make a GET request to /v1/{platform}/{resource}, start pulling social data. The unified schema means your first integration is the only one you write.
Visual Explorer. No API key needed. Paste any social URL and see the full response.
AI Agent. Install the Skill with one command, or add the MCP config block to Claude or Cursor. Structured, enriched social data flows into your agent with no bespoke integration.

Credits never expire. No artificial rate limits. Most endpoints cost 1 credit per request. Advanced endpoints (demographics, AI transcripts) cost 5 or 10. Plans scale from free through Starter, Growth, Pro, and Enterprise as your usage grows.

FAQ

What is a social media data API?

A service that retrieves publicly available data from social platforms and returns it in a structured format. SocialCrawl goes one step further: it normalizes every platform's response into a single unified schema, so you write one integration and it works across all 21 platforms.

Why can't I just use platform APIs directly?

Each platform has its own auth, rate limits, schema, and pagination. At one platform it's manageable. At two it's annoying. At ten it's a full-time job. SocialCrawl abstracts all of it — authentication, normalization, pagination, rate-limit handling — so one GET request gets you consistent data regardless of source.

How does SocialCrawl work with AI agents like Claude?

Via MCP server or Skill install. Add one config block to any MCP-compatible client (Claude Desktop, Cursor) and the agent can query social data directly. For agent harnesses like Claude Code or Codex, the Skill installs in one command. Data arrives in a unified schema with computed fields already calculated, so agents reason on it directly with no custom parsing logic.

What data do I actually get from the API?

Profiles, posts, comments, search results, and analytics across 21 platforms and 108 endpoints. Every response includes computed fields: engagement_rate, estimated_reach, content_category, and language. Most endpoints cost 1 credit per request. Credits never expire, and you can add ?format=raw to any request to get the unprocessed upstream response alongside the unified schema.

How much does SocialCrawl cost?

Start free with 100 credits, no credit card. Most endpoints cost 1 credit per request. Advanced endpoints cost 5 or 10 credits. Credits never expire and there are no artificial rate limits. Paid plans scale from Starter through Growth, Pro, and Enterprise. Pay as you go, no subscription required.

I launched SocialCrawl this weekend. Got my first paying customer within 24 hours of launch, from a reply on Threads. The agent I built SocialCrawl for is the one that surfaced the post I replied to. The loop closed on itself.

I haven't perfectly solved the "telling the world about what I ship" problem — you're reading this, so some of it is working — but the system runs now. If there's a social platform I haven't added yet and you need it, tell me and I'll try to add it quickly. If you want to try the API I built because I needed it: 100 credits, no credit card.

Happy hacking.

— Oscar

How to Use Claude Agents: A Developer's Guide to Managed Agents, Sub-agents, and Real-time Data

A developer's guide to Claude Managed Agents, Claude Code sub-agents, and the Messages API. Setup in 4 steps, parallel execution, MCP, rate limits.

The OpenAI Assistants API in 2026: A Field Guide to the Shutdown, the Migration, and What Comes Next

OpenAI shuts down the Assistants API on 26 August 2026. A practical migration guide: Responses API, costs, frameworks, and the realistic timeline.

Browse AI Web Scraper: Where It Wins, and Where Social Data APIs Fit Better

Browse AI is great for web pages; social platforms need a specialist. Decision guide for developers choosing scrapers vs unified social-data APIs.