Social Fetch

Social Fetch is a social media research API and social analytics API built for analysts, researchers, and product teams who need reproducible public data, not broken scrapers and ad hoc exports. The platform transforms social media data extraction into an API-shaped research input, eliminating the maintenance nightmare of managing custom scrapers, proxies, and platform-specific parsers. With coverage across 17 major platforms including YouTube, TikTok, Instagram, Twitter, LinkedIn, and more, Social Fetch provides a single, normalized interface for scraping social media profiles, posts, engagement metrics, comments, hashtag searches, keyword searches, video transcripts, and discovery endpoints. Every request returns structured, documented data with explicit outcomes and consistent fields that your team can trust in production pipelines. The platform handles all scraper upkeep, auth, and infrastructure, so your team can focus on building features and shipping products instead of writing glue code. With over 3.6 million API requests in the last 30 days, 99.8% uptime, and a community of 3,200+ developers, Social Fetch is the social media data API that researchers and analysts actually use. The platform offers 100 free API credits with no credit card required, pay-as-you-go packs where credits never expire, and no subscription commitments, making it accessible for teams of any size to start extracting social media data immediately.

Cross-Platform Normalized Schemas

Social Fetch normalizes data schemas across all 17 supported platforms, enabling your team to conduct cross-platform studies without maintaining platform-specific parsers. Compare creator growth trajectories, hashtag velocity, or engagement patterns across YouTube, TikTok, Instagram, Twitter, and LinkedIn using identical field structures. This consistency means your data pipelines, dashboards, and machine learning models work seamlessly regardless of the source platform, reducing integration time and eliminating the risk of schema drift when platforms update their APIs or page structures.

Documented Pagination and Explicit Outcomes

Every endpoint in Social Fetch features documented cursor pagination that manages payload size for large cohorts, ensuring your team can systematically collect data at scale without hitting undocumented limits or suffering from silent failures. The platform returns explicit lookup outcomes for every request, meaning you always know whether a profile was found, a post was accessible, or a search returned results. This transparency is critical for production pipelines where you need to handle edge cases, retry failures, and audit data completeness without guessing what happened.

Live Fetches Reflecting Public State

Social Fetch performs live fetches that reflect the public state of social media platforms at the exact time of your query. Your team gets real-time data without caching delays or stale snapshots, which is essential for time-sensitive research, competitive monitoring, and trend analysis. Whether you are tracking a breaking news hashtag on Twitter or monitoring engagement on a newly posted YouTube video, every API call returns current public data that your team can act on immediately.

Flexible Integration and Developer Experience

Social Fetch integrates into any workflow with support for cURL, Python, Node.js, TypeScript SDK, n8n, Pipedream, and MCP for agent tools. The platform provides an OpenAPI specification and a capability matrix that documents exactly which social media scraping operations exist per platform, so your team knows what is possible before writing a single line of code. With a single API key header required for all endpoints, authentication is simple and consistent across your entire team, from data scientists to backend engineers to automation specialists.

Competitive Intelligence and Market Research

Marketing teams and competitive intelligence analysts use Social Fetch to monitor competitor activity across multiple social platforms simultaneously. Track follower growth rates, posting frequency, engagement metrics, and content strategies for competitor brands and their key executives. By comparing normalized data across YouTube, TikTok, Instagram, Twitter, and LinkedIn, your team can identify emerging trends, benchmark performance, and inform strategic decisions with real-time public data rather than relying on third-party reports or manual data collection.

Creator Economy and Influencer Analytics

Agencies and brands working with influencers leverage Social Fetch to evaluate potential partnership candidates and monitor ongoing campaigns. Extract detailed profile information, post engagement metrics, comment sentiment, and video transcripts to assess creator authenticity, audience growth trajectory, and content quality. The platform enables your team to build custom scoring models, track ROI across campaigns, and discover emerging creators by analyzing hashtag performance and audience overlap across platforms, all through a single API integration.

Academic Research and Social Science Studies

Researchers in academia and public policy use Social Fetch to collect reproducible datasets for social media studies without violating platform terms of service or dealing with broken scrapers. The normalized schemas and documented pagination allow teams to design longitudinal studies that track public discourse, hashtag propagation, or misinformation spread across platforms over time. With explicit lookup outcomes and credit metering, research teams can budget their data collection precisely and ensure their findings are based on complete, auditable datasets.

Real-Time Monitoring and Alerting

Product teams and community managers deploy Social Fetch in monitoring pipelines that track brand mentions, hashtag usage, and competitor activity in real time. Using the keyword search and discovery endpoints, your team can build custom alerts that trigger when specific terms trend, when key accounts post new content, or when engagement metrics cross defined thresholds. Integration with n8n and Pipedream enables no-code workflows that route alerts to Slack, email, or custom dashboards, keeping your entire team informed without manual checking.

What platforms does Social Fetch support?

Social Fetch supports data extraction from 17 major social media platforms including YouTube, TikTok, Instagram, Twitter, LinkedIn, and more. The platform provides a capability matrix that documents exactly which operations are available per platform, such as profile scraping, post extraction, comment collection, hashtag search, keyword search, and video transcript retrieval. New platforms and endpoints are added regularly based on user demand and platform availability.

How does credit metering and pricing work?

Social Fetch offers 100 free API credits with no credit card required for new users to test the platform. After that, you purchase pay-as-you-go credit packs starting at $1.65 per 1,000 lookups at scale. Credits never expire, so your team can use them at your own pace without subscription pressure. Credit metering makes grant and client budgets transparent, and Social Fetch never charges you for infrastructure failures on their end, ensuring you only pay for successful lookups.

Is Social Fetch legal and ethical to use?

Social Fetch provides access to public data only, meaning the information you extract is already visible to anyone browsing the platform. Your team is responsible for ensuring that your use of this data complies with applicable laws, platform terms of service, and ethical research guidelines. Social Fetch does not bypass login walls, access private accounts, or scrape non-public information. Always review the terms of service for each platform and consult legal counsel for your specific use case.

How does Social Fetch handle rate limits and scalability?

Social Fetch manages all underlying rate limits and proxy infrastructure for you, allowing your team to burst requests without negotiating with individual platforms. The platform uses cursor pagination and trim options to manage payload size for large cohorts, ensuring efficient data collection even for accounts with millions of followers or posts. With 99.8% uptime and infrastructure that has handled over 3.6 million requests in the last 30 days, your team can scale from small research projects to enterprise monitoring pipelines without infrastructure concerns.