Agent-Reach

Overview

Agent-Reach is a powerful CLI tool that extends AI agents' capabilities by enabling them to search and read content from multiple social platforms and websites. It provides unified access to Twitter/X, Reddit, YouTube, GitHub, Bilibili, and XiaoHongShu (小红书), allowing agents to gather real-time information from across the internet without requiring individual API keys or incurring per-platform costs.

With over 29,000 GitHub stars, Agent-Reach has quickly become one of the most popular tools for extending AI agent intelligence beyond their training data cutoff.

Features

• Multi-Platform Search: Search across Twitter, Reddit, YouTube, GitHub, Bilibili, and XiaoHongShu with a single CLI command
• Zero API Fees: No need to manage individual API keys or pay per-platform API costs
• CLI-First Design: Simple command-line interface that's easy to integrate into any agent workflow
• Structured Output: Returns well-formatted results that agents can easily parse and use
• Real-Time Data: Access current information from social platforms and communities

Installation

pip install agent-reach

Quick Start

from agent_reach import AgentReach

# Initialize the agent
reach = AgentReach()

# Search Twitter for recent discussions
results = reach.search_twitter(query="AI agents", limit=10)

# Search Reddit for relevant threads
reddit_results = reach.search_reddit(query="machine learning", limit=5)

# Search YouTube for video content
video_results = reach.search_youtube(query="deep learning tutorial", limit=5)

# Search GitHub for relevant repositories
github_results = reach.search_github(query="agent framework", limit=5)

# Search Bilibili for Chinese video content
bilibili_results = reach.search_bilibili(query="AI教程", limit=5)

# Search XiaoHongShu for lifestyle content
xiaohongshu_results = reach.search_xiaohongshu(query="AI工具", limit=5)

Core Concepts

Unified Search Interface

Agent-Reach provides a consistent API across all supported platforms. Each search method returns structured data with titles, URLs, snippets, and metadata appropriate to the platform.

Zero-Cost Architecture

Unlike platform-native APIs that require API keys and charge per request, Agent-Reach uses web scraping and public data sources to retrieve information without API costs.

Advanced Features

Combined Search

# Search all platforms simultaneously
all_results = reach.search_all(
    query="artificial intelligence trends",
    platforms=["twitter", "reddit", "youtube"],
    limit=5
)

Content Reading

# Read full content from a specific URL
content = reach.read_url("https://reddit.com/r/...")

Rate Limiting and Caching

# Configure rate limits and caching
reach = AgentReach(
    rate_limit=10,  # requests per second
    cache_ttl=3600  # cache results for 1 hour
)

Examples

Research Agent

from agent_reach import AgentReach

reach = AgentReach()

# Gather market intelligence
market_data = {
    "twitter": reach.search_twitter(query="AI market trends", limit=20),
    "reddit": reach.search_reddit(query="AI investment", limit=10),
    "youtube": reach.search_youtube(query="AI market analysis", limit=5),
}

# Process and summarize results
for platform, results in market_data.items():
    print(f"\n=== {platform.upper()} ===")
    for item in results:
        print(f"- {item['title']}: {item['url']}")

Competitive Intelligence

# Track competitor mentions
competitor_mentions = reach.search_twitter(
    query="competitor_name AI product launch",
    since="2026-06-01"
)

Pros

• ✅ Massive platform coverage — 6+ platforms in one tool
• ✅ Zero API costs — no per-platform API key required
• ✅ Simple CLI interface — easy to integrate
• ✅ Highly popular — 29,000+ GitHub stars
• ✅ Great for research agents — real-time information gathering

Cons

• ❌ Fragile to platform changes — may break when platforms update their interfaces
• ❌ No official API support — relies on scraping/public data
• ❌ Rate limits vary — each platform has different limits
• ❌ Limited to public content — cannot access private or authenticated data

When to Use

• Building research or intelligence-gathering agents
• Need real-time social media data without API costs
• Creating market analysis or competitive intelligence tools
• Developing content aggregation agents

Resources

• GitHub Repository
• PyPI Package
• Documentation