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Bocha Web Search▌

by intounknown

Bocha Web Search offers advanced features using a Google web search API for real-time, customizable internet results and

Enables AI to perform web searches with customizable parameters including freshness filters, domain controls, and result summarization for retrieving up-to-date information from the internet.

github stars

★ 3

0 commentsdiscussion

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

Time-based freshness filtersDomain filtering controlsBuilt-in result summarization

best for

/ AI assistants needing current web information
/ Research and fact-checking applications
/ Content creation requiring up-to-date data

capabilities

/ Search the web with customizable queries
/ Filter results by time periods (day, week, month, year)
/ Include or exclude specific domains
/ Generate summarized search results
/ Control number of results returned

what it does

Provides web search capabilities to AI assistants through the Bocha API with customizable filters for freshness, domains, and result summarization.

about

Bocha Web Search is a community-built MCP server published by intounknown that provides AI assistants with tools and capabilities via the Model Context Protocol. Bocha Web Search offers advanced features using a Google web search API for real-time, customizable internet results and It is categorized under search web.

how to install

You can install Bocha Web Search 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

Apache-2.0

Bocha Web Search is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

mcp-bocha

A Model Context Protocol (MCP) server that provides web search capabilities to AI agents using the Bocha API.

<a href="https://glama.ai/mcp/servers/@intounknown/mcp-bocha"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@intounknown/mcp-bocha/badge" alt="MCP-Bocha MCP server" /> </a>

Introduction

MCP-Bocha is a tool that exposes Bocha AI's web search API capabilities through the Model Context Protocol. It allows AI assistants to search the web programmatically, enabling tasks such as information retrieval, research, and up-to-date data collection.

Tools

Tool Name	Description	Parameters
`mcp-bocha_search`	Search the web for information	`query`: The search query string<br>`freshness`: Optional time filter ["oneDay", "oneWeek", "oneMonth", "oneYear", "noLimit"]<br>`summary`: Optional boolean for summarized results<br>`include`: Optional array of domains to include<br>`exclude`: Optional array of domains to exclude<br>`count`: Optional number of results to return

Usage

{
  "mcpServers": {
    "mcp-bocha": {
      "command": "npx",
      "args": ["-y", "@humansean/mcp-bocha"],
      "env": {
        "BOCHA_API_KEY": "YOUR_API_KEY"
      }
    }
  }
}

License

Apache-2.0 license

FAQ

What is the Bocha Web Search MCP server?: Bocha Web Search 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 Bocha Web Search?: This profile displays 57 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 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.Install web automation MCP server via npm or pip
2.Configure allowed domains and rate limits in MCP config
3.Test with simple fetch: 'Get content from example.com'
4.Progress to extraction: 'Extract all product prices from this page'
5.Set up monitoring: 'Check this URL daily for changes'
6.Parse structured data: 'Create CSV from this table'
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.

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MCP server reviews

Ratings

4.6★★★★★57 reviews

★★★★★Kwame Smith· Dec 28, 2024
Bocha Web Search is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
★★★★★Maya Jackson· Dec 24, 2024
We evaluated Bocha Web Search against two servers with overlapping tools; this profile had the clearer scope statement.
★★★★★Li Yang· Dec 24, 2024
Bocha Web Search is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
★★★★★Chaitanya Patil· Dec 8, 2024
Bocha Web Search is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
★★★★★Anaya Sanchez· Dec 8, 2024
Bocha Web Search has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
★★★★★Piyush G· Nov 27, 2024
We evaluated Bocha Web Search against two servers with overlapping tools; this profile had the clearer scope statement.
★★★★★Mateo Li· Nov 27, 2024
Bocha Web Search reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
★★★★★Zaid Rahman· Nov 19, 2024
We evaluated Bocha Web Search against two servers with overlapping tools; this profile had the clearer scope statement.
★★★★★Li Chen· Nov 15, 2024
Bocha Web Search is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
★★★★★Carlos Ghosh· Nov 15, 2024
Useful MCP listing: Bocha Web Search is the kind of server we cite when onboarding engineers to host + tool permissions.

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