Social Fetch

Social Fetch is the social media scraper API built specifically for the AI era. While most social data tools return messy HTML or require you to manage fragile scrapers, proxies, and rate limits, Social Fetch delivers clean, structured JSON for every major platform. Think of it as the missing data layer for AI agents. With over 3.6 million lookups in the last 30 days and 3,200+ developers already onboard, Social Fetch has become the go-to infrastructure for teams that need live social media data without the headache of maintaining scraper pipelines. Whether you are building a creator research tool, a competitive intelligence dashboard, a sentiment analysis engine, or an AI agent that needs to look up influencers on the fly, Social Fetch gives you one API to rule them all. It covers 17+ platforms including YouTube, TikTok, Instagram, Twitter, LinkedIn, and more. Every request hits the live platform and returns typed fields, documented schemas, and consistent error envelopes. No more guessing if a 200 response actually means data was found. Social Fetch includes explicit lookupStatus fields and shared requestId across all endpoints so you can debug and trust every response in production. The platform is optimized for agent workflows with a hosted MCP server for Cursor and Claude, a TypeScript SDK with Result types, and synchronous REST endpoints that just work. Start with 100 free credits, no credit card required, and scale with pay-as-you-go pricing that never expires. Social Fetch is the social media data API for products that prompt agents to look up creators, not maintain scraper infrastructure.

Agent-Friendly Data Contracts

Every endpoint returns structured JSON with typed fields, documented schemas, and consistent error handling. Social Fetch uses shared error envelopes that include a requestId for debugging and an explicit lookupStatus field. This means an HTTP 200 does not automatically mean the data was found. You get clear indicators for empty or ambiguous results, making it safe to use in automated agent pipelines without manual validation. The TypeScript SDK further enhances this with Result types for predictable error handling.

17+ Platform Coverage

One integration replaces the chaos of stitching together multiple marketplace scrapers. Social Fetch covers YouTube, TikTok, Instagram, Twitter, LinkedIn, and more with endpoints for profile scraping, post metadata, comment scraping, engagement metrics, transcripts, hashtag API search, keyword search, and competitive ad-library queries. Whether you need a creator's follower count, a video's transcript, or ad spend data, it is all available through a single API key and consistent request format.

Live Data, Every Request

Unlike cached or stale data providers, Social Fetch hits the live platform on every single request. This means you always get the most current follower counts, engagement metrics, and profile information. The infrastructure handles proxies, rate limits, and anti-bot measures so your team never has to deal with those headaches. With 99.8% uptime and burst capacity without throttling, you can scale from a single lookup to millions without changing a line of code.

MCP Server for AI Agents

Social Fetch includes a hosted Model Context Protocol (MCP) server that integrates directly with Cursor, Claude, and custom agent frameworks. This means your AI agents can scrape social media profiles, posts, and search results as naturally as asking a question. No complex API wrappers or middleware needed. The MCP server handles authentication, request formatting, and response parsing so your agents get clean data they can act on immediately.

Creator Research and Vetting

Marketing teams and agencies use Social Fetch to instantly pull comprehensive profiles of potential influencer partners. With a single API call, you get follower counts, engagement rates, bio information, verification status, and recent post performance across platforms. This replaces hours of manual research and spreadsheet work with automated, reliable data that feeds directly into your CRM or decision-making tools.

Competitive Intelligence and Market Research

Brands and analysts use Social Fetch to monitor competitors across social platforms. Track follower growth trends, analyze post engagement, and compare ad library activity. The keyword and hashtag search endpoints let you discover emerging trends and conversations in real time. This data feeds dashboards, reports, and AI models that help teams make faster, data-driven decisions about content strategy and market positioning.

AI Agent and LLM Data Enrichment

Developers building AI agents and LLM-powered products use Social Fetch as the data layer for social media lookups. When an agent needs to find a creator's latest post, verify a profile, or pull engagement metrics, Social Fetch provides the structured data the model can reason over. The MCP server integration means agents in Cursor or Claude can fetch live social data without leaving their workflow, making them dramatically more useful for research and analysis tasks.

Sentiment Analysis and Brand Monitoring

PR and customer insights teams use Social Fetch to collect real-time comments, post metadata, and engagement data for sentiment analysis pipelines. By scraping comments and post interactions across platforms, you can build models that detect brand sentiment, identify emerging issues, and track campaign performance. The structured JSON output feeds directly into NLP models and dashboards without the need for custom HTML parsers.

What platforms does Social Fetch support?

Social Fetch covers 17+ major social media platforms including YouTube, TikTok, Instagram, Twitter (X), LinkedIn, and more. Each platform has dedicated endpoints for profiles, posts, comments, and engagement metrics. The platform list is continuously expanding based on customer demand. Check the documentation for the most up-to-date list of supported platforms and available endpoints.

How does the free tier work and what are the pricing options?

Social Fetch offers 100 free credits upon signup with no credit card required. This lets you test the API thoroughly before committing. After that, pricing is pay-as-you-go starting at $1.65 per 1,000 requests at scale. Credits never expire, and you can burst requests without negotiating rate limits. You only pay for successful lookups, and you are never charged for infrastructure failures on Social Fetch's side.

Is the data live or cached?

Every request to Social Fetch hits the live platform in real time. There is no caching layer that serves stale data. This ensures you always get the most current follower counts, engagement metrics, profile information, and post content. The infrastructure handles all the complexity of proxies, rate limits, and anti-bot measures so your data is always fresh and reliable.

How do I integrate Social Fetch with AI agents like Cursor or Claude?

Social Fetch provides a hosted MCP (Model Context Protocol) server that integrates directly with Cursor, Claude, and custom agent frameworks. You simply configure the MCP server endpoint and your API key, and your agents can scrape social media data as naturally as asking a question. The SDKs for TypeScript, Python, and Node.js also make traditional REST integration straightforward for custom applications.