AUTOMATION · Agents & IoT
Equip AI Agents with Free Multi-Platform Social Crawling via Open-Source Agent-Reach MCP
A viral multi-platform social extraction engine with 100k+ stars on GitHub! Agent-Reach gives AI agents eyes across the entire social web. Through a unified MCP server and CLI, agents can search, read, and extract posts, comments, and transcripts from Twitter/X, Reddit, YouTube, GitHub, Bilibili, and XiaoHongShu—with zero platform API fees and zero authentication headaches for automated social listening and competitor audits.
CORE TOOLS
Agent-Reach (Open Source), Model Context Protocol (MCP), Python 3.10+, Claude Code / Cursor
BEST FOR
Growth marketers, social media managers, indie product creators, competitive intelligence analysts, AI agent developers
REQUIREMENTS
Python 3.10+, internet access to target social platforms, and an MCP-compatible agent environment (Claude Code, Cursor, Windsurf).
✦ WHY THIS WORKFLOW
Commercial social APIs are prohibitively expensive and fragmented across closed silos. Agent-Reach bridges the gap through a clean, open MCP layer, allowing coding and research agents to monitor unvarnished user opinions without recurring API bills.
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Step-by-Step Action Checklist
0 / 4 Completed
READY-TO-USE PROMPT TEMPLATE
I am using open-source Agent-Reach to conduct cross-platform competitive sentiment research on AI coding tools. Please provide: 1) [Agent-Reach MCP Configuration]: Production-ready mcpServers JSON snippet for Claude Code and Cursor with custom rate-limiting and user-agent rotation parameters; 2) [Multi-Platform Sentiment Extraction Prompt]: Prompt directing the agent to crawl Twitter, Reddit, and Bilibili over the last 14 days, categorizing insights into pricing complaints, usability bottlenecks, and churn intent; 3) [Automated Sentiment Briefing Script]: Python script formatting extracted social mentions into a structured executive markdown table comparing engagement metrics and negative-to-positive sentiment ratios.