Use when universal internet scraper for AI agents. Read and search Twitter,
Scanned 9/8/2026
Install to Claude Code
npx -y skills add oyi77/1ai-skills --skill agent-reach --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: agent-reach
description: Use when universal internet scraper for AI agents. Read and search Twitter,
Reddit, YouTube, GitHub, Bilibili, XiaoHongShu, LinkedIn, V2EX, RSS, web pages.
Zero API fees. Use when agents need real-time social media data, content research,
or trend monitoring.
domain: mcp
author: oyi77
license: Apache-2.0
subdomain: mcp
tags:
- agent
- ai-agent
- api
- github
- mcp-server
- model-context-protocol
- monitoring
- reach
version: 1.0.0
category: mcp
---
# Agent Reach
## When to Use
**Trigger phrases:**
- "agent reach"
- "Scrape Twitter tweets, threads, search results without API keys"
- "Read Reddit posts, comments, subreddit feeds"
- "Get YouTube video transcripts and metadata"
- Scrape Twitter tweets, threads, search results without API keys
- Read Reddit posts, comments, subreddit feeds
- Get YouTube video transcripts and metadata
- Scrape XiaoHongShu (Little Red Book) posts
- Monitor Bilibili video content
- Search across platforms for competitive intelligence
- Gather social proof and sentiment data
- Research trending content for viral creation
- **When NOT to use**: When you already have API access (use native tools), when the platform blocks scraping ethically, when data doesn't need real-time freshness
## When NOT to Use
- When a simpler HTTP client would suffice
- For internal tools that do not need cross-platform compatibility
- When the tool is used by a single agent in a single context
## Overview
Agent Reach implements a Model Context Protocol server for Model Context Protocol.
## Architecture
- **Server** — MCP-compliant server exposing tools and resources
- **Transport** — stdio or HTTP transport layer
- **Tools** — Callable functions with JSON Schema definitions
- **Resources** — Readable data sources with URI-based access
## Setup
1. Install the MCP server package
2. Configure environment variables and credentials
3. Register the server in MCP client configuration
4. Test tool invocations and resource access
## Configuration
- Server name and version
- Transport type (stdio, SSE, HTTP)
- Tool definitions with input/output schemas
- Resource URI patterns
- Authentication and rate limiting
## Integration
- Compatible with Claude, Cursor, and other MCP clients
- Supports streaming responses for large payloads
- Handles errors with standard MCP error codes
## Anti-Rationalization Table
| Rationalization | Reality |
|---|---|
| "I will just use curl" | MCP handles auth, retries, streaming, and type safety. Use the SDK. |
| "One mega-server is simpler" | Single-responsibility servers are easier to debug and maintain. |
| "MCP is just a wrapper" | MCP enables cross-platform tool sharing. It is infrastructure, not overhead. |
```typescript
// Example: MCP server tool definition
import { McpServer } from "@modelcontextprotocol/sdk";
const server = new McpServer({ name: "my-tools", version: "1.0.0" });
server.tool("search", { query: z.string() }, async ({ query }) => {
const results = await search(query);
return { content: [{ type: "text", text: JSON.stringify(results) }] };
});
```
## Process
1. **Prepare** — Gather requirements, verify prerequisites, set up environment
1. **Execute** — Run agent reach workflow with configured parameters
1. **Verify** — Validate output meets requirements, document results
## Verification
- [ ] All steps executed successfully
- [ ] Results validated against acceptance criteria
- [ ] Error handling tested with edge cases
- [ ] Documentation updated with findingsIs this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
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