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ScraperSocial API

For AI agents

ScraperSocial is built to be consumed by agents: transcripts and summaries are first-class, responses are compact JSON with stable keys, and every capability is exposed as a tool.

Option 1 — MCP server (recommended)

One config block gives any MCP client the full surface:

{
  "mcpServers": {
    "scrapersocial": {
      "url": "https://mcp.scrapersocial.com",
      "headers": { "Authorization": "Bearer sk_live_..." }
    }
  }
}

OAuth 2.1 (PKCE) is also supported — clients like claude.ai can connect with no key at all. In Claude Code:

Terminal window
claude mcp add --transport http scrapersocial https://mcp.scrapersocial.com

Tools exposed

get_transcript, get_summary, get_post_stats, get_comments, get_profile, get_channel_posts, search_tiktok, search_instagram_reels. Each takes a URL or handle (plus platform where ambiguous) and returns the same envelope as REST.

Option 2 — function-calling tools

Wrap any endpoint in your framework of choice:

def get_tiktok_transcript(url: str) -> dict:
    """Transcript of a public TikTok video, with timestamped segments."""
    r = httpx.get("https://api.scrapersocial.com/v1/tiktok/transcript",
                  params={"url": url},
                  headers={"Authorization": f"Bearer {KEY}"}, timeout=120)
    r.raise_for_status()
    return r.json()["data"]

Tips that make agents behave:

  • Use format=text for transcripts headed straight into a prompt.
  • Use fields= projections to keep tool results token-cheap.
  • Surface error.message to the model — messages are written to be self-correcting (“It may be private or deleted”).

Discovery endpoints

Agents can find everything without a human:

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