Vercel AI SDK

SocialCrawl has no dedicated AI SDK provider, and it does not need one: the API is a single authenticated GET request, so you wrap it in a tool() and hand it to generateText. One tool gives your agent live access to 42 platforms.

How do I give a Vercel AI SDK agent social media data?

Define a tool with a zod inputSchema that takes a platform, a resource, and the endpoint's params, then call the SocialCrawl REST API inside execute with your key in the x-api-key header. Pass the tool to generateText (or streamText) and set stopWhen so the model can call the tool and then answer.

// socialcrawl-ai-sdk.ts
// Run with: SOCIALCRAWL_API_KEY=sc_... ANTHROPIC_API_KEY=... npx tsx socialcrawl-ai-sdk.ts
import { generateText, tool, stepCountIs } from "ai";
import { anthropic } from "@ai-sdk/anthropic";
import { z } from "zod";

const API_KEY = process.env.SOCIALCRAWL_API_KEY;
if (!API_KEY) throw new Error("Set SOCIALCRAWL_API_KEY");

const socialcrawl = tool({
  description:
    "Fetch live social media, commerce, and review data from SocialCrawl. " +
    "Covers TikTok, Instagram, YouTube, LinkedIn, Reddit, Amazon and more. " +
    "Set `platform` (e.g. 'tiktok'), `resource` (e.g. 'profile'), and `params` " +
    "(the endpoint's query fields, e.g. { handle: 'charlidamelio' }).",
  inputSchema: z.object({
    platform: z.string().describe("Platform slug, e.g. 'tiktok' or 'youtube'"),
    resource: z.string().describe("Endpoint resource, e.g. 'profile' or 'search'"),
    params: z
      .record(z.string(), z.union([z.string(), z.number()]))
      .describe("Query parameters for the endpoint"),
  }),
  execute: async ({ platform, resource, params }) => {
    const url = new URL(`https://www.socialcrawl.dev/v1/${platform}/${resource}`);
    for (const [key, value] of Object.entries(params ?? {})) {
      url.searchParams.set(key, String(value));
    }
    const res = await fetch(url, { headers: { "x-api-key": API_KEY } });
    return res.json();
  },
});

const { text } = await generateText({
  model: anthropic("claude-sonnet-4-5"),
  tools: { socialcrawl },
  // Let the model call the tool, then answer with the result.
  stopWhen: stepCountIs(5),
  maxOutputTokens: 1024,
  prompt: "How many followers does @charlidamelio have on TikTok?",
});

console.log(text);

Install the packages first (check the AI SDK docs for the current versions):

npm install ai @ai-sdk/anthropic zod

The tool uses inputSchema (the AI SDK v6 field, not parameters) and the call uses maxOutputTokens (not maxTokens). Swap anthropic("claude-sonnet-4-5") for any provider model the AI SDK supports; the tool definition does not change.

Why one tool instead of one per endpoint?

Every SocialCrawl endpoint shares the same shape: a GET at /v1/{platform}/{resource} with query parameters and one x-api-key header, returning the same JSON envelope. A single tool that takes platform, resource, and params therefore reaches all 325 endpoints without a new tool per call. Point the model at the platform directory or the machine-readable llms.txt so it knows which values to pass, and it will pick the right endpoint on its own.

How do I control credit spend?

The tool spends credits only on a live request, billed exactly as the REST API bills: standard endpoints are 1 credit, transcripts and other premium endpoints are 10 credits, and the universal search/everywhere call is a flat 20 credits. Empty results and upstream errors are auto-refunded, and cache hits cost 0 credits. The response envelope includes credits_remaining so you can surface spend to the user. See Credits and Endpoint pricing for the full table.

Where to go next

• Get a key at socialcrawl.dev (100 free credits) and read Authentication.
• Prefer LangChain? The same pattern in that framework is on the LangChain page.
• Using an MCP client instead? Claude Code and Skills & MCP skip the DIY tool entirely.
• Explore the platform directory or start with the Quickstart.