WEBSEARCH_INTEGRATION_SUMMARY.txtβ’9.5 kB
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β β
β β¨ WebSearch-MCP Integration Successfully Completed! β¨ β
β β
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Reference: https://mcpservers.org/servers/mnhlt/WebSearch-MCP
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π¦ WHAT WAS CREATED:
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β
docker-compose.yml
β Docker configuration for WebSearch crawler + FlareSolverr
β Uses Mac Apple Silicon compatible images
β
start_websearch.sh (executable)
β Helper script to start Docker services
β Includes health checks and status monitoring
β
test_websearch.py (executable)
β Comprehensive test script for web search functionality
β Tests basic search, news, and weather queries
β
WEBSEARCH_SETUP.md
β Complete documentation for WebSearch setup
β Architecture diagrams
β Troubleshooting guide
β Docker commands reference
β
QUICKSTART.md
β 5-minute quick start guide
β Step-by-step instructions
β Common commands and troubleshooting
β
web_search.py (UPDATED)
β Now uses WebSearch-MCP crawler API
β Rich results with metadata
β Advanced filtering (all, news, blogs)
β Language and region support
β Cloudflare bypass capability
β
ReadMe.md (UPDATED)
β Added WebSearch features documentation
β Updated prerequisites (Docker, etc.)
β Added quick setup instructions
β
.env (UPDATED)
β Added WEBSEARCH_API_URL=http://localhost:3001
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π― FEATURES YOU NOW HAVE:
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π Real-Time Web Search
β’ Production-ready crawler service
β’ Google search integration
β’ Rich metadata (titles, snippets, URLs, authors, sources)
π Cloudflare Bypass
β’ FlareSolverr integration
β’ Access to protected websites
β’ Automatic CAPTCHA handling
π° Advanced Filtering
β’ All results (general web)
β’ News articles only
β’ Blog posts only
β’ Language filtering
β’ Region-specific results
π Rich Results
β’ Page titles
β’ Content snippets
β’ Full URLs
β’ Site names
β’ Author/byline information
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π HOW TO START USING IT:
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STEP 1: Start Docker Desktop
β’ Open Docker Desktop app
β’ Wait for it to be fully running (Docker icon in menu bar)
STEP 2: Start WebSearch Services
cd ~/Desktop/Programming_llms/model_context_protocol
./start_websearch.sh
STEP 3: Wait 30-60 seconds for services to initialize
STEP 4: Test the Setup
uv run python test_websearch.py
STEP 5: Use in Your AI Assistant
uv run python ai_chat_assistant.py
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π¬ EXAMPLE QUERIES TO TRY:
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In your AI assistant, try asking:
β’ "Search the web for Python 3.12 new features"
β’ "What's the latest news about SpaceX?"
β’ "Search for React best practices 2025"
β’ "Find articles about quantum computing"
β’ "What's the weather in San Francisco?"
β’ "Search for AAPL stock price"
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π DOCUMENTATION:
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π QUICKSTART.md β 5-minute setup guide
π WEBSEARCH_SETUP.md β Detailed WebSearch documentation
π ReadMe.md β Complete project documentation
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ποΈ ARCHITECTURE:
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User Question
β
AI Assistant
(ai_chat_assistant.py)
β
Python MCP Server
(web_search.py)
β HTTP POST
WebSearch Crawler API
(Docker: localhost:3001)
β
FlareSolverr
(Cloudflare Bypass)
β
π Internet
(Google, News, Blogs)
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π³ DOCKER SERVICES:
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Service 1: websearch-api
β’ Image: laituanmanh/websearch-crawler:latest
β’ Port: 3001
β’ Purpose: Web crawling and search
Service 2: flaresolverr
β’ Image: 21hsmw/flaresolverr:nodriver
β’ Port: 8191
β’ Purpose: Bypass Cloudflare protection
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βοΈ USEFUL COMMANDS:
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Start Services:
./start_websearch.sh
OR: docker-compose up -d
Stop Services:
docker-compose down
Check Status:
docker-compose ps
View Logs:
docker-compose logs -f
Test API:
curl http://localhost:3001/health
Restart:
docker-compose restart
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β οΈ IMPORTANT NOTES:
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β’ Docker Desktop MUST be running for web search to work
β’ First search may take 10-20 seconds (containers warming up)
β’ Subsequent searches are faster (2-5 seconds)
β’ Services use ~500MB RAM
β’ Stop services when done to save resources: docker-compose down
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π YOU'RE ALL SET!
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Your Personal AI Assistant now has production-grade web search capabilities!
Next: Start Docker Desktop, run ./start_websearch.sh, and enjoy real-time
web searching in your AI assistant!
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