search-web

TongXiao IQS

aliyun

by aliyun

TongXiao IQS delivers real-time, accurate web search by integrating IQS APIs and advanced language models for diverse, c

Integrates with TongXiao's IQS APIs to provide enhanced real-time web search capabilities that deliver clean, accurate, and diverse results through multiple data sources optimized with large language models.

github stars

5

0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Multiple data sources integratedLLM-optimized resultsReal-time web search

best for

  • / AI assistants needing current web information
  • / Applications requiring high-quality search results
  • / Research tools needing diverse data sources

capabilities

  • / Search real-time web content
  • / Query multiple data sources simultaneously
  • / Retrieve clean and accurate search results
  • / Access diverse vertical data sources
  • / Get LLM-optimized search responses

what it does

Provides enhanced real-time web search through TongXiao's IQS APIs that deliver clean, accurate results from multiple data sources optimized with large language models.

about

TongXiao IQS is an official MCP server published by aliyun that provides AI assistants with tools and capabilities via the Model Context Protocol. TongXiao IQS delivers real-time, accurate web search by integrating IQS APIs and advanced language models for diverse, c It is categorized under search web.

how to install

You can install TongXiao IQS in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

TongXiao IQS is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

TongXiao Common Search MCP Server

A Model Context Protocol (MCP) server implementation that integrates with IQS APIs, which delivers clean, accurate, diverse, and high-quality results through multiple data sources. For more Information about TongXiao, please visit our documents.

Installation

NPM Installation

npm install -g @tongxiao/common-search-mcp-server

Running with npx

# run stdio server
env TONGXIAO_API_KEY=your-api-key npx -y @tongxiao/common-search-mcp-server
# run sse server
env TONGXIAO_API_KEY=your-api-key SERVER=sse npx -y @tongxiao/common-search-mcp-server

You can find your apikey from ipaas.console.aliyun.com/api-key

Running on client

Configure Tongxiao MCP Server directly on mainstream MCP Client.

{
    "mcpServers": {
        "tongxiao-common-search": {
            "command": "npx",
            "args": [
                "-y",
                "@tongxiao/common-search-mcp-server"
            ],
            "env": {
                "TONGXIAO_API_KEY": ""
            }
        }
    }
}

Available Tools

  1. common_search This tool offers enhanced real-time search capabilities for open domain networks. By utilizing optimization with large models and integrating multiple data sources, it delivers clean, accurate, diverse, and high-quality results.

Best for: When you are unsure where to find information, use this interface to obtain accurate information from the web or multiple vertical data sources.

FAQ

What is the TongXiao IQS MCP server?
TongXiao IQS is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for TongXiao IQS?
This profile displays 39 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.

Use Cases

Web Research & Information Gathering

Fetch and extract information from websites automatically

Example

Research competitor pricing, scrape product reviews, monitor news mentions

Automate 5-10 hours/week of manual web research

Content Monitoring & Alerts

Track website changes, new content, price updates

Example

Monitor competitor blog for new posts, track stock availability, watch for pricing changes

Stay informed without manual checking, never miss important updates

Data Extraction & Aggregation

Extract structured data from multiple websites

Example

Compile product listings from 10 e-commerce sites, aggregate job postings, collect real estate data

Build datasets 100x faster than manual copying

API-less Integration

Interact with services that don't offer APIs

Example

Check form submissions, validate website functionality, test user flows

Automate interactions with any website, even without API

Implementation Guide

Prerequisites

  • Claude Desktop or Cursor with MCP support
  • Understanding of web scraping ethics and robots.txt
  • Rate limiting awareness to avoid overwhelming target sites
  • Knowledge of legal restrictions on data collection

Time Estimate

20-40 minutes including configuration and testing

Installation Steps

  1. 1.Install web automation MCP server via npm or pip
  2. 2.Configure allowed domains and rate limits in MCP config
  3. 3.Test with simple fetch: 'Get content from example.com'
  4. 4.Progress to extraction: 'Extract all product prices from this page'
  5. 5.Set up monitoring: 'Check this URL daily for changes'
  6. 6.Parse structured data: 'Create CSV from this table'
  7. 7.Respect robots.txt and rate limits always

Troubleshooting

  • 403 Forbidden: Website blocks bots—respect their wishes, use official API instead
  • Rate limit errors: Slow down requests, add delays between fetches
  • Stale data: Target site changed HTML structure—update selectors
  • Timeout errors: Site is slow or blocking—increase timeout, try different user agent
  • JavaScript-rendered content: Use headless browser MCP servers for dynamic sites

Best Practices

✓ Do

  • +Check robots.txt and respect crawl rules
  • +Rate limit requests: 1-2 requests/second maximum
  • +Use official APIs when available instead of scraping
  • +Identify your bot with descriptive user agent
  • +Cache results to minimize repeated requests
  • +Handle errors gracefully with retries and fallbacks
  • +Validate extracted data for accuracy

✗ Don't

  • Don't scrape sites that explicitly forbid it (robots.txt, ToS)
  • Don't overwhelm servers with rapid requests—use rate limiting
  • Don't scrape personal data without consent and legal basis
  • Don't ignore copyright on extracted content
  • Don't assume HTML structure is stable—handle changes
  • Don't use scraped data for commercial purposes without permission

💡 Pro Tips

  • Use CSS selectors or XPath for robust data extraction
  • Set up monitoring alerts for extraction failures (structure changed)
  • Implement exponential backoff for retries on failures
  • Store raw HTML for reprocessing if extraction logic changes
  • Combine with data analysis tools for insights from extracted data
  • Consider using official APIs or RSS feeds as more stable alternatives

Technical Details

Architecture

MCP server handles HTTP requests, HTML parsing, JavaScript rendering (if headless browser), and returns structured data to Claude.

Protocols

  • HTTP/HTTPS
  • WebSocket (for real-time sites)
  • Puppeteer/Playwright (for JavaScript sites)

Compatibility

  • Static HTML sites
  • JavaScript-rendered SPAs (with headless browser)
  • REST APIs
  • GraphQL endpoints

When to Use This

✓ Use When

Use for research automation, content monitoring, data aggregation from multiple sources, and when official APIs don't exist. Best for read-only information gathering.

✗ Avoid When

Avoid for sites with APIs (use API instead), sites that explicitly forbid scraping, when data is copyrighted, or for login-required content without proper authorization.

Integration

  • Scheduled monitoring with change detection
  • Multi-source data aggregation pipelines
  • Fallback to web scraping when API rate limits hit
  • Headless browser for JavaScript-heavy sites

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

List & Promote Your MCP Server

Share your MCP server with the developer community

GET_STARTED →
MCP server reviews

Ratings

4.539 reviews
  • Pratham Ware· Dec 28, 2024

    We evaluated TongXiao IQS against two servers with overlapping tools; this profile had the clearer scope statement.

  • Isabella Bansal· Dec 28, 2024

    TongXiao IQS is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Zara Diallo· Dec 24, 2024

    TongXiao IQS has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Aanya Wang· Dec 12, 2024

    TongXiao IQS is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Yash Thakker· Nov 19, 2024

    TongXiao IQS has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Aanya Li· Nov 19, 2024

    Useful MCP listing: TongXiao IQS is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Aditi Farah· Nov 15, 2024

    We evaluated TongXiao IQS against two servers with overlapping tools; this profile had the clearer scope statement.

  • Aanya Chen· Nov 3, 2024

    According to our notes, TongXiao IQS benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Aditi Brown· Oct 22, 2024

    TongXiao IQS has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Dhruvi Jain· Oct 10, 2024

    According to our notes, TongXiao IQS benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

showing 1-10 of 39

1 / 4