Show HN: MyLocalAI now has Google Search – Local AI with web access

2 hours ago 2

A Next.js chat application powered by LangGraph with MCP (Model Context Protocol) tools for real-time web search and data access. Features Server-Sent Events (SSE) streaming for real-time AI responses. Completely local and open source.

🎥 Watch Demo

Next.js 15 - Modern React framework with App Router
LangGraph - AI agent framework for complex reasoning workflows
MCP Tools - Google search, web scraping, and data access tools
SSE Streaming - Real-time response streaming via Server-Sent Events
Ollama - Local LLM hosting (Qwen 3 14B recommended)

User Message → LangGraph Agent → MCP Tools (Web Search) → LLM → SSE Stream → UI

🚀 Advanced AI Capabilities

✅ LangGraph Agent - Complex reasoning and tool usage
✅ Real-time Web Search - Current information via Google Search
✅ Web Scraping - Extract content from specific URLs
✅ SSE Streaming - Real-time response updates
✅ Tool Call Visibility - See when AI uses external tools

✅ Markdown Rendering - Rich text responses with code highlighting
✅ Conversation History - Persistent chat threads
✅ Multiple Sessions - Manage multiple conversations
✅ Real-time Status - Live updates during processing

✅ Completely Local - AI runs on your hardware
✅ No API Keys Required - Uses local Ollama instance
✅ Thread Management - SQLite-based conversation storage
✅ Debug Mode - Detailed logging and performance metrics

# macOS brew install ollama # Windows/Linux # Visit https://ollama.com for installer

2. Install Required Model

ollama pull qwen3:4b # Alternative: ollama pull qwen3:4b

Navigate to http://localhost:3000

RAM: 16GB+ (recommended for Qwen 3 14B)
CPU: Modern multi-core processor
Storage: 10GB+ free space for models

Node.js: v18+ (v20+ recommended)
Ollama: Latest version
Modern Browser: Chrome, Firefox, Safari, Edge

Next.js 15 - React framework with App Router
LangGraph - AI agent framework (@langchain/langgraph ^0.4.9)
MCP SDK - Model Context Protocol (@modelcontextprotocol/sdk ^1.18.1)
Ollama LangChain - Local LLM integration (@langchain/ollama ^0.2.4)
SQLite Checkpointer - Conversation persistence (@langchain/langgraph-checkpoint-sqlite ^0.2.1)

Edit app/page.tsx to change the model:

const requiredModel = 'qwen3:4b'; // or 'qwen3:4b', 'llama3.1:70b', etc.

Google Search (google_search)

Purpose: Get current information from web search
Usage: Automatically used for current events, facts, news
Parameters: query (string)

Purpose: Extract content from specific URLs
Usage: Get detailed information from websites
Parameters: url (string)

Purpose: Generate random numbers
Usage: Games, randomization, decision making
Parameters: sides (number), count (number)

make prod # Install, build, and start production server make dev # Development server with hot reload make clean # Clean build artifacts make help # Show all available commands

app/ ├── components/ # React components │ ├── ChatInterface.tsx # Main chat UI │ ├── ChatList.tsx # Conversation sidebar │ └── StatusBanner.tsx # Connection status indicator ├── langraph_backend/ # LangGraph API routes │ ├── route.ts # Main SSE streaming endpoint │ ├── schemas.ts # Request/response validation │ ├── lib/ # Utilities and checkpointer │ └── conversations/ # Thread management API │ ├── route.ts # List conversations │ └── [thread_id]/route.ts # Get/delete specific conversation ├── mcp_server/ # MCP tool implementations │ ├── [transport]/ # MCP protocol handler │ │ └── route.ts # Tool registration and routing │ ├── tools/ # Individual tool definitions │ │ ├── googleSearch.ts # Google search tool │ │ ├── scrape.ts # Web scraping tool │ │ └── rollDice.ts # Random number generator │ ├── search/ # Google search implementation │ └── scrape/ # Web scraping implementation ├── utils/ # Shared utilities │ └── localStorage.ts # Browser storage helpers ├── layout.tsx # Root layout component └── page.tsx # Main chat page