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Social Fetch
Social Fetch is a unified scraping API and Model Context Protocol (MCP) data service that provides structured access to public social media data. Developers and AI agent engineers use Social Fetch to extract profiles, posts, comments, video transcripts, and engagement metrics across networks like TikTok, Instagram, YouTube, X, and LinkedIn without managing proxy pools or parsers. By normalizing multi-platform payloads into a single JSON schema with zero-retention privacy, Social Fetch accelerates social monitoring, creator tools, and LLM data pipeline development.
What it does
• Extracts public profiles, posts, comments, engagement metrics, and video transcripts across 13+ social networks. • Normalizes multi-platform data into a single, predictable JSON envelope across all supported platform endpoints. • Connects natively with coding agents and LLMs via a hosted Model Context Protocol (MCP) HTTP server. • Provides real-time upstream fetches with built-in retry handling and automatic error credit refunds.
Why it works
Single API integration replaces fragile multi-vendor scraper stacks and custom proxy maintenance workflows. Unified JSON schema eliminates custom platform glue code and reduces data parsing overhead. Pay-as-you-go credit pricing model with non-expiring credits removes fixed monthly subscription commitments. Native Model Context Protocol (MCP) server enables AI coding agents like Cursor and Claude to fetch live social data directly.
Category: AI & Automation
Team Size: 1
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As of 2026
AI & Automation
Revenue: 0-$100k ARR
Unified social media scraping API providing structured data across major platforms.
Overview
Social Fetch is a unified scraping API and Model Context Protocol (MCP) data service that provides structured access to public social media data. Developers and AI agent engineers use Social Fetch to extract profiles, posts, comments, video transcripts, and engagement metrics across networks like TikTok, Instagram, YouTube, X, and LinkedIn without managing proxy pools or parsers. By normalizing multi-platform payloads into a single JSON schema with zero-retention privacy, Social Fetch accelerates social monitoring, creator tools, and LLM data pipeline development.
Funding status: Bootstrapped
Revenue source: Usage-based
Customer type: B2B
Pricing: Usage-based
Tech stack: TypeScript, Node.js, REST API, Model Context Protocol (MCP), Cloud Infrastructure
Platform: Web
Integrations: TikTok, Instagram, YouTube, X (Twitter), LinkedIn, Reddit, Facebook, Spotify, Telegram, Threads, Cursor, VS Code, Claude Code, Windsurf, Model Context Protocol (MCP)
Founder story
Social Fetch was created by developer Luke Askew to solve the engineering tax of building and maintaining custom social media scrapers. After repeatedly spending dozens of engineering hours fixing broken scrapers, rate limits, and fragile proxy pools across constantly changing social platforms, he built Social Fetch as a single, unified REST API and MCP server. The platform gives SaaS developers and AI agents a reliable, normalized pipeline for public social data.
What it does
- • Extracts public profiles, posts, comments, engagement metrics, and video transcripts across 13+ social networks
- • Normalizes multi-platform data into a single, predictable JSON envelope across all supported platform endpoints
- • Connects natively with coding agents and LLMs via a hosted Model Context Protocol (MCP) HTTP server
- • Provides real-time upstream fetches with built-in retry handling and automatic error credit refunds.
Who it's for
- AI Agent Developers & LLM Engineers
- SaaS Founders & Full-Stack Engineers
- Social Analytics & Monitoring Teams
- Growth Hackers & Brand Researchers
Why it works
- Single API integration replaces fragile multi-vendor scraper stacks and custom proxy maintenance workflows
- Unified JSON schema eliminates custom platform glue code and reduces data parsing overhead
- Pay-as-you-go credit pricing model with non-expiring credits removes fixed monthly subscription commitments
- Native Model Context Protocol (MCP) server enables AI coding agents like Cursor and Claude to fetch live social data directly.
Growth strategies
- Developer community distribution through Product Hunt, GitHub, and AI coding marketplaces
- Content marketing around scraper architecture, API reliability, and LLM web data extraction
- MCP server integration capturing developer adoption inside Cursor, VS Code, and Windsurf environments
- Self- serve developer onboarding offering 100 free credits without requiring credit card registration
Alternatives
Comparison overview
- Social Fetch provides a normalized multi-network API with non-expiring pay-as-you-go credits and a native MCP server for AI coding agents.
- Alternative platforms like Apify or Bright Data often require managing custom actor scripts, proxy pools, and complex enterprise monthly commitments.