Give Claude & ChatGPT Real-Time Social Vision.
Large Language Models are incredibly smart, but they are stuck in the past without live data. Through the Model Context Protocol, your AI agents can securely, natively, and instantly scrape, analyze, and read data from every major social network.
How AI agents read the social web
Claude Desktop App
Connect directly to your local Claude Desktop client. Ask Claude to "Scrape the comments on this YouTube link" or "Audit this TikTok profile bio" and watch it retrieve the data dynamically.
Custom LLM Workflows
Building automated agents with LangChain, LlamaIndex, or AutoGen? Connect our secure protocol endpoints to feed live, structured social statistics into your agent decision loops.
Token-Optimized Format
We manage the infrastructure, rate-limits, and scraping layers. Raw HTML is filtered out: our servers deliver highly condensed, text-only context designed specifically to save LLM tokens.
Everything your AI can read
Equip your assistant with tools to pull clean, structured data across 6 major social networks.
YouTube
Extract full video transcripts and deep channel metrics.
- Fetch channel statistics and subscriber metadata
- Retrieve precise video transcripts and subtitles
- List and filter long-form videos & Shorts
- Pull paginated comment sections for sentiment analysis
TikTok
Access creator profiles and trending video transcripts.
- Scrape complete profile data, bios, and stats
- Retrieve and paginate through creator video lists
- Extract exact video captions and descriptions
- Pull native video comments and search creators
Analyze public Reels, feed posts, and audience comments.
- Extract follower counts, profiles, and bio links
- Scrape public Reels, feed posts, and carousels
- Fetch precise engagement rates and post stats
- Pull recent user comments and post descriptions
X (Twitter)
Read user threads and analyze media attachments.
- Retrieve detailed user profiles and metrics
- Fetch recent tweet timelines and multi-post threads
- Extract media transcripts from video posts
- Audit public tweets for specific keyword topics
Understand company pages and professional updates.
- Scrape company pages and employee counts
- Retrieve recent posts from company page feeds
- Fetch engagement stats on professional posts
- Audit user profile metrics and histories
Monitor community discussions and trending topics.
- Access subreddit descriptions and community rules
- Pull trending, top, or latest subreddit posts
- Fetch deep, nested comment trees for analysis
- Search keywords globally across all of Reddit
Stop building scrapers. Give your agents vision.
To ensure high performance, reliability, and dedicated support, we are selectively granting access. Fill out the application form below and our team will get back to you within 24 hours.
Commonly asked questions
By offering concise and informative responses, this section helps users find solutions without the need to contact customer support, saving time
The Model Context Protocol (MCP) is an open standard designed to let AI systems like Claude Desktop and ChatGPT query databases or local APIs. Our MCP integration lets your LLMs query live social media data securely in real time.
When you ask a question like 'what did this creator post on TikTok yesterday?', the LLM calls our MCP server, which safely fetches the public profile, transcribes the video if needed, and returns the cleaned text directly to your AI's context.
Yes. All requests are authenticated via secure API keys and run over TLS. We only fetch public social media data and do not store any credentials or user access tokens.
Anthropic's Claude Desktop is natively supported out of the box. You can also connect it to OpenAI's custom GPTs, LangChain/LlamaIndex agents, AutoGen setups, or any other agent framework that implements the standard MCP client.
We handle 100% of proxy rotation, session maintenance, CAPTCHA solving, and rate limiting. Your AI agent receives clean, structured data without you needing to manage any scraping infrastructure.
Yes, you can connect directly via standard REST APIs, but the MCP server is specifically optimized to format and compress response payloads to save your LLM token budget.