Docs Navigator SUSE Edition
БесплатноНе проверенAn AI-powered documentation navigator that enables intelligent search, summarization, and exploration of SUSE, Rancher, and related open-source documentation us
Описание
An AI-powered documentation navigator that enables intelligent search, summarization, and exploration of SUSE, Rancher, and related open-source documentation using local or cloud AI models.
README

An AI-powered documentation navigator built as a Model Context Protocol (MCP) server that enables intelligent search, summarization, and exploration of SUSE, Rancher, K3s, RKE2, Longhorn, Harvester, NeuVector, and Kubewarden documentation using open-source AI models.
✨ New: Production-ready with SQLite caching, advanced analytics, concurrent indexing support, and organized codebase!
🎨 View Live Demo - Check out the UI demo on GitHub Pages!
📚 Documentation
- Architecture Overview - System design and components
- Installation Guide - Detailed setup instructions
- Documentation Sources - All available sources and usage guide
- Indexing Guide - Understanding caching vs indexing ⭐
- Quick Reference - Command reference
- Usage Examples - Common usage patterns
- Web GUI Guide - Web interface documentation
- MCP Client Setup - Configure MCP clients
- SQLite Migration Guide - SQLite caching details
- Change Detection - Auto-update system for monitoring doc changes ⭐
- GitHub Pages Deployment - Deploy UI showcase to GitHub Pages
- Contributing - Contribution guidelines
🌟 Features
Core Capabilities
- 🌐 Web GUI - Beautiful localhost web interface for easy access
- 🔍 Semantic Documentation Search - Find relevant docs using natural language queries
- 🤖 Local Open-Source AI - Powered by Ollama (Llama, Mistral, etc.) - no API keys required
- 📚 Multi-Source Support - Navigate SUSE, Rancher, K3s, RKE2, Longhorn, Harvester, NeuVector, Kubewarden documentation
- 💬 Conversational Interface - Ask questions and get answers with source citations
- 📝 Smart Summarization - Generate concise or detailed summaries of documentation
- 🔌 MCP Protocol - Integrates with Claude Desktop and other MCP-compatible clients
- ⚡ Vector Search - Fast semantic retrieval using embeddings
- 🎯 Flexible AI Providers - Support for Ollama (local), OpenAI, or Anthropic
Production Features (NEW!)
- 💾 SQLite Caching - Efficient page caching with SQLite for scaling to 1000s of documents
- 📊 Analytics Reports - Comprehensive cache analytics and health monitoring
- 🔍 Advanced Queries - Filter cached documents by source, status, date range
- 🔒 Concurrent Indexing - Safe multi-process indexing with automatic locking
- 📈 Cache Management - Validate, clear, rebuild, and optimize caches
- 🎯 Smart Indexing - Conditional GET requests, ETag/Last-Modified support, content hash detection
- 🔄 Change Detection - Monitor docs for updates and auto-trigger re-indexing
- 📦 Organized Codebase - Clean directory structure with CLI/services/tests/utils separation
🏗️ Architecture
graph TB
subgraph "Client Layer"
WEB[🌐 Web Browser<br/>localhost:3000]
CLAUDE[🤖 Claude Desktop<br/>MCP Client]
CLI[⌨️ CLI Tools<br/>npm commands]
end
subgraph "Application Layer"
WEBSERVER[🖥️ Web Server<br/>Express.js<br/>Port 3000]
MCP[📡 MCP Server<br/>index.js<br/>stdio protocol]
CLITOOLS[🛠️ CLI Tools<br/>indexer, analytics,<br/>cache manager]
end
subgraph "Service Layer"
DOCSERVICE[📚 Documentation Service<br/>- Fetch & Parse HTML<br/>- Content Extraction<br/>- Sitemap Processing]
AISERVICE[🧠 AI Service<br/>- LLM Integration<br/>- Prompt Management<br/>- Response Formatting]
VECTORSERVICE[🔍 Vector Service<br/>- Embedding Generation<br/>- Semantic Search<br/>- Similarity Ranking]
CACHESERVICE[💾 Cache Service<br/>- SQLite Operations<br/>- Page Management<br/>- Lock Handling]
end
subgraph "Storage Layer"
SQLITE[(🗄️ SQLite Database<br/>page-cache.db<br/>- Pages Table<br/>- Locks Table)]
VECTORS[(📊 Vector Index<br/>vectra/index.json<br/>- Embeddings<br/>- Metadata)]
HTMLCACHE[📁 HTML Cache<br/>data/html/<br/>cached pages]
end
subgraph "External Services"
OLLAMA[🦙 Ollama<br/>Local LLMs<br/>localhost:11434]
OPENAI[🌐 OpenAI API<br/>GPT Models<br/>Embeddings]
ANTHROPIC[🔷 Anthropic API<br/>Claude Models]
DOCS[📖 Documentation Sites<br/>- docs.k3s.io<br/>- ranchermanager.docs<br/>- documentation.suse.com<br/>- etc.]
end
%% Client connections
WEB -->|HTTP/REST API| WEBSERVER
CLAUDE -->|stdio/MCP| MCP
CLI -->|Node.js| CLITOOLS
%% Application layer connections
WEBSERVER -->|Use Services| DOCSERVICE
WEBSERVER -->|Use Services| AISERVICE
WEBSERVER -->|Use Services| VECTORSERVICE
MCP -->|Use Services| DOCSERVICE
MCP -->|Use Services| AISERVICE
MCP -->|Use Services| VECTORSERVICE
CLITOOLS -->|Use Services| DOCSERVICE
CLITOOLS -->|Use Services| CACHESERVICE
%% Service layer connections
DOCSERVICE -->|Read/Write| CACHESERVICE
DOCSERVICE -->|Fetch| DOCS
DOCSERVICE -->|Store HTML| HTMLCACHE
AISERVICE -->|Query LLM| OLLAMA
AISERVICE -->|Query LLM| OPENAI
AISERVICE -->|Query LLM| ANTHROPIC
VECTORSERVICE -->|Generate Embeddings| OLLAMA
VECTORSERVICE -->|Generate Embeddings| OPENAI
VECTORSERVICE -->|Read/Write| VECTORS
CACHESERVICE -->|SQL Operations| SQLITE
%% Styling
classDef clientStyle fill:#e1f5ff,stroke:#01579b,stroke-width:2px
classDef appStyle fill:#f3e5f5,stroke:#4a148c,stroke-width:2px
classDef serviceStyle fill:#e8f5e9,stroke:#1b5e20,stroke-width:2px
classDef storageStyle fill:#fff3e0,stroke:#e65100,stroke-width:2px
classDef externalStyle fill:#fce4ec,stroke:#880e4f,stroke-width:2px
class WEB,CLAUDE,CLI clientStyle
class WEBSERVER,MCP,CLITOOLS appStyle
class DOCSERVICE,AISERVICE,VECTORSERVICE,CACHESERVICE serviceStyle
class SQLITE,VECTORS,HTMLCACHE storageStyle
class OLLAMA,OPENAI,ANTHROPIC,DOCS externalStyle
Key Components
- Web GUI: Modern React-like interface for interactive documentation search
- MCP Server: Model Context Protocol implementation for Claude Desktop integration
- CLI Tools: Command-line utilities for indexing, analytics, and cache management
- Documentation Service: Handles fetching, parsing, and caching of documentation pages
- AI Service: Manages LLM interactions with support for multiple providers (Ollama, OpenAI, Anthropic)
- Vector Service: Generates embeddings and performs semantic search using Vectra
- Cache Service: SQLite-based caching system with locking for concurrent operations
🆕 Recent Updates (December 2025)
Phase 3: Production-Ready SQLite Migration
What's New:
SQLite Caching System
- Migrated from JSON to SQLite for better scalability
- Support for 1000s of documents without performance degradation
- Automatic schema creation with indexes on source, status, timestamps
- Backward compatible - can revert to JSON with
USE_JSON_CACHE=true
Advanced Analytics & Queries
npm run analytics- Comprehensive cache health reportsnpm run query-cache- Filter by source, status, date range- Cache efficiency metrics, stale page detection, automated recommendations
- By-source breakdowns showing indexed/total ratios
Concurrent Indexing Safety
- Table-based locking prevents race conditions
- 30-minute lock timeout with automatic expiration
npm run clear-locksfor manual lock cleanup- Safe to run multiple indexing processes simultaneously
Organized Codebase
- Clean directory structure:
cli/,services/,tests/,utils/ - 15 files reorganized from root into logical folders
- Better maintainability and developer experience
- Comprehensive documentation in
src/README.md
- Clean directory structure:
Performance Optimizations
- Smart caching with ETag/Last-Modified support
- Content hash detection skips unchanged documents
- Sitemap optimization pre-filters URLs before fetching
- Conditional GET requests reduce unnecessary downloads
Migration:
- Existing users: Run
npm run migrate-sqliteto convert JSON cache - New users: SQLite is default, no action needed
- See docs/SQLITE_MIGRATION.md for details
🚀 Quick Start
Prerequisites
- Node.js 18+ - Download here
- Ollama (for local AI) - Download here
- OpenAI API Key (optional) - For production embeddings
Step 1: Install Dependencies
# Clone the repository
git clone https://github.com/mso-docs/Docs-Navigator-MCP-SUSE-Edition.git
cd Docs-Navigator-MCP-SUSE-Edition
# Install Node.js dependencies
npm install
Step 2: Install AI Models
Option A: Local AI with Ollama (Free, Recommended for Q&A)
# Install Ollama from https://ollama.ai
# Pull required models
ollama pull llama3.2:latest # For answering questions
ollama pull nomic-embed-text # For embeddings (alternative)
# Verify Ollama is running
ollama list
Option B: OpenAI (Recommended for Embeddings)
# Get API key from https://platform.openai.com/api-keys
# Add to .env file: OPENAI_API_KEY=your_key_here
Hybrid Approach (Best Performance):
- Use OpenAI for embeddings (fast, reliable)
- Use Ollama for Q&A (free, private)
Step 3: Configure Environment
# Copy example environment file
cp .env.example .env
# Edit .env with your settings
nano .env # or use your favorite editor
Essential Configuration:
# For Ollama-only setup
AI_PROVIDER=ollama
EMBEDDING_PROVIDER=ollama
OLLAMA_MODEL=llama3.2:latest
EMBEDDING_MODEL=nomic-embed-text
# For OpenAI embeddings + Ollama Q&A (Recommended)
AI_PROVIDER=ollama
EMBEDDING_PROVIDER=openai
OPENAI_API_KEY=sk-your-key-here
OLLAMA_MODEL=llama3.2:latest
# Cache settings (SQLite is default)
PAGE_CACHE_PATH=./data/page-cache.db
EMBEDDING_CACHE_PATH=./data/embedding-cache.json
Step 4: Index Documentation
# Index all documentation sources (SUSE, Rancher, K3s)
npm run index all
# Or index individual sources
npm run index k3s
npm run index rancher
npm run index suse
First-time indexing takes 5-15 minutes depending on your internet speed and AI provider. Subsequent runs are much faster due to caching.
Step 5: Start Using!
Web Interface (Easiest):
npm run web
Then open http://localhost:3000 in your browser.
MCP Server (for Claude Desktop):
npm start
See docs/MCP_CLIENT_CONFIG.md for Claude Desktop setup.
🎉 You're Ready!
Try asking questions like:
- "How do I install K3s on SUSE?"
- "What are the differences between K3s and RKE2?"
- "Show me Rancher backup procedures"
See docs/EXAMPLES.md for more usage examples.
🛠️ Available Tools
The MCP server provides these tools:
search_docs
Search documentation using semantic search.
{
"query": "How do I install K3s on SUSE?",
"source": "all",
"limit": 5
}
ask_question
Ask questions about documentation and get AI-generated answers with sources.
{
"question": "What are the differences between K3s and RKE2?",
"context": "deployment on SUSE Linux Enterprise"
}
summarize_doc
Generate AI summaries of documentation pages.
{
"url": "https://docs.k3s.io/installation",
"format": "bullet-points"
}
get_doc_section
Retrieve specific documentation content.
{
"url": "https://documentation.suse.com/sles/15-SP5/"
}
index_documentation
Index documentation for faster searching.
{
"source": "k3s",
"forceRefresh": false
}
list_doc_sources
View all available documentation sources and their status.
📖 Usage Examples
Web Interface (Easiest!)
Start the web interface and access it from your browser:
npm run web
Then open http://localhost:3000 in your browser. See docs/WEB_GUI.md for details.
With Claude Desktop
- Configure Claude Desktop (see docs/INSTALL.md)
- Ask Claude to use the tools:
"Can you search the SUSE documentation for information about container security?"
"Use the docs navigator to find K3s installation instructions"
"Summarize the Rancher high availability setup documentation"
Direct MCP Usage
# Start the MCP server
npm start
# The server communicates via stdio using MCP protocol
Command-Line Tools
# Indexing
npm run index [source] # Index documentation (k3s, rancher, suse, all)
npm run index all # Index all sources
npm run index k3s --force # Force refresh (ignore cache)
# Cache Management
npm run stats # Show cache statistics
npm run analytics # Comprehensive analytics report
npm run query-cache [opts] # Query cache with filters
npm run clear-cache # Clear all caches
npm run validate # Validate cache integrity
npm run clear-locks # Clear expired indexing locks
# Utilities
npm run fix-sources # Fix legacy cache entries
npm run mark-indexed # Mark documents as indexed
npm run migrate-sqlite # Migrate JSON cache to SQLite
# Testing
npm test # Run test suite
🏗️ Architecture
┌─────────────────────────────────────────────────────────────┐
│ User Interfaces │
├─────────────────┬─────────────────┬──────────────────────────┤
│ Web Browser │ Claude Desktop │ Direct MCP Client │
│ (port 3000) │ (MCP stdio) │ (stdio/JSON) │
└────────┬────────┴────────┬────────┴────────┬─────────────────┘
│ │ │
▼ ▼ ▼
┌─────────────────────────────────────────────────────────────┐
│ Application Layer (Node.js) │
├─────────────────┬───────────────────────┬───────────────────┤
│ web-server.js │ index.js (MCP) │ CLI Tools │
│ (Express) │ (stdio protocol) │ (index-docs.js) │
└────────┬────────┴───────────┬───────────┴────────┬──────────┘
│ │ │
└────────────────────┼────────────────────┘
▼
┌─────────────────────────────────────────────────────────────┐
│ Service Layer │
├──────────────────┬──────────────────┬──────────────────────┤
│ AI Service │ Vector Service │ Doc Service │
│ - Ollama Q&A │ - Vectra DB │ - HTTP fetching │
│ - OpenAI embed │ - Embeddings │ - HTML parsing │
│ - Summarization │ - Similarity │ - Cache management │
└────────┬─────────┴────────┬─────────┴──────────┬───────────┘
│ │ │
▼ ▼ ▼
┌─────────────────────────────────────────────────────────────┐
│ Data Layer │
├───────────────┬─────────────────┬────────────────────────────┤
│ SQLite Cache │ Vectra Vectors │ Embedding Cache (JSON) │
│ - Page cache │ - Doc chunks │ - Text hash → vector │
│ - Metadata │ - Embeddings │ - Fast deduplication │
└───────────────┴─────────────────┴────────────────────────────┘
Key Components
- MCP Server (
index.js): Implements Model Context Protocol for tool execution via stdio - Web Server (
web-server.js): Express server providing browser-based UI - AI Service: Handles LLM interactions for Q&A and summarization (Ollama/OpenAI/Anthropic)
- Cache Service: SQLite-based page caching with advanced queries and analytics
- Vector Service: Manages semantic search using Vectra vector database
- Documentation Service: Fetches, parses, and indexes documentation with smart caching
Data Flow
- Indexing: Docs → Fetch → Parse → Chunk → Embed → Store in Vectra + Cache
- Searching: Query → Embed → Vector Search → Retrieve Docs → Return Results
- Q&A: Question → Context Search → LLM → Answer with Citations
🔧 Configuration
Edit .env to configure:
# AI Provider (ollama, openai, anthropic)
AI_PROVIDER=ollama
# Ollama Settings
OLLAMA_BASE_URL=http://localhost:11434
OLLAMA_MODEL=llama3.2:latest
EMBEDDING_MODEL=nomic-embed-text
# Documentation Sources
SUSE_DOCS_BASE_URL=https://documentation.suse.com
RANCHER_DOCS_URL=https://ranchermanager.docs.rancher.com
K3S_DOCS_URL=https://docs.k3s.io
# Vector Database
VECTOR_DB_PATH=./data/vectors
📁 Project Structure
Docs-Navigator-MCP-SUSE-Edition/
├── docs/ # Documentation files
│ ├── ARCHITECTURE.md # System design and components
│ ├── INSTALL.md # Detailed installation guide
│ ├── QUICKREF.md # Command quick reference
│ ├── EXAMPLES.md # Usage examples
│ ├── WEB_GUI.md # Web interface guide
│ ├── MCP_CLIENT_CONFIG.md # MCP client configuration
│ ├── SQLITE_MIGRATION.md # SQLite caching guide
│ └── CONTRIBUTING.md # Contribution guidelines
│
├── scripts/ # Setup and utility scripts
│ ├── setup.sh # Linux/macOS setup script
│ └── setup.bat # Windows setup script
│
├── src/ # Source code (organized by purpose)
│ ├── cli/ # Command-line tools
│ │ ├── index-docs.js # Main indexing CLI
│ │ ├── cache-analytics.js # Analytics reports
│ │ ├── query-cache.js # Cache queries
│ │ └── clear-locks.js # Lock management
│ │
│ ├── services/ # Core business logic
│ │ ├── ai-service.js # AI/LLM integration
│ │ ├── cache-service.js # SQLite cache management
│ │ ├── documentation-service.js # Doc fetching & parsing
│ │ └── vector-service.js # Vector database ops
│ │
│ ├── tests/ # Test scripts
│ │ ├── test.js # Main test suite
│ │ ├── test-cache.js # Cache tests
│ │ ├── test-concurrent-locks.js # Lock tests
│ │ └── test-ollama.js # Ollama integration tests
│ │
│ ├── utils/ # Maintenance utilities
│ │ ├── migrate-to-sqlite.js # JSON→SQLite migration
│ │ ├── fix-cache-sources.js # Cache repair tools
│ │ └── mark-indexed.js # Status updates
│ │
│ ├── index.js # MCP server entry point
│ └── web-server.js # Web UI server
│
├── public/ # Web GUI assets (HTML, CSS, JS)
├── data/ # Data storage
│ ├── vectors/ # Vector database (Vectra)
│ ├── page-cache.db # SQLite page cache
│ ├── embedding-cache.json # Embedding cache
│ └── html/ # Cached HTML files
│
└── .env # Environment configuration
🔧 Troubleshooting
Installation Issues
Problem: npm install fails
# Clear npm cache and retry
npm cache clean --force
rm -rf node_modules package-lock.json
npm install
Problem: Node.js version too old
# Check version (needs 18+)
node --version
# Update Node.js from https://nodejs.org/
# Or use nvm:
nvm install 18
nvm use 18
Ollama Issues
Problem: "Connection refused" or "ECONNREFUSED"
# Check if Ollama is running
curl http://localhost:11434/api/tags
# Start Ollama
ollama serve
# Or check Ollama is installed
ollama --version
Problem: Models not found
# List installed models
ollama list
# Pull required models
ollama pull llama3.2:latest
ollama pull nomic-embed-text
# Verify models work
ollama run llama3.2:latest "Hello"
Problem: Ollama too slow
# Use OpenAI for embeddings instead
# Edit .env:
EMBEDDING_PROVIDER=openai
OPENAI_API_KEY=your_key_here
# Keep Ollama for Q&A (free and private)
AI_PROVIDER=ollama
Indexing Issues
Problem: Indexing fails with "Item already exists"
# This happens with parallel indexing - use sequential mode
# In .env file:
FETCH_BATCH_SIZE=1
# Or clear vectors and reindex
npm run clear-cache
npm run index all
Problem: "Another indexing process is already running"
# Clear stale locks
npm run clear-locks
# Then retry indexing
npm run index all
Problem: Indexing very slow
# Use OpenAI embeddings (much faster than Ollama)
# Edit .env:
EMBEDDING_PROVIDER=openai
OPENAI_API_KEY=your_key_here
# Ollama embeddings take ~30 min for 110 docs
# OpenAI embeddings take ~2 min for same docs
Problem: "404 Not Found" during indexing
# Some documentation URLs may have changed
# Check cache analytics for details
npm run analytics
# Rebuild specific source
npm run rebuild suse
Cache Issues
Problem: UI shows "0 documents indexed"
# Check actual cache status
npm run stats
# If cache exists but UI shows 0, restart web server
npm run web
# If genuinely empty, index documentation
npm run index all
Problem: Outdated cached content
# Force refresh all caches
npm run index all --force
# Or clear and reindex
npm run clear-cache
npm run index all
Problem: Cache corruption
# Validate cache integrity
npm run validate
# If errors found, rebuild
npm run clear-cache
npm run migrate-sqlite # If migrating from JSON
npm run index all
Web Interface Issues
Problem: Web server won't start
# Check if port 3000 is in use
lsof -i :3000 # Linux/Mac
netstat -ano | findstr :3000 # Windows
# Kill process using port 3000 or change port
# Edit src/web-server.js: const PORT = 3001;
Problem: "No results found" in web UI
# Verify documents are indexed
npm run stats
# Check AI service is working
npm test
# Verify Ollama/OpenAI connection
curl http://localhost:11434/api/tags # Ollama
MCP Server Issues
Problem: Claude Desktop can't connect
# Verify MCP server starts
npm start
# Check Claude Desktop config file location:
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%\Claude\claude_desktop_config.json
# Validate config syntax (must be valid JSON)
# See docs/MCP_CLIENT_CONFIG.md for examples
Problem: Tools not appearing in Claude
# Restart Claude Desktop completely
# Check server logs for errors
npm start 2>&1 | tee server.log
Performance Issues
Problem: Slow searches
# Check cache stats
npm run analytics
# Ensure documents are indexed
npm run stats
# Try rebuilding vector index
npm run clear-cache vectors
npm run index all
Problem: High memory usage
# Reduce batch sizes in .env:
FETCH_BATCH_SIZE=1
EMBEDDING_CONCURRENCY=1
# Or use OpenAI embeddings (more efficient)
EMBEDDING_PROVIDER=openai
Database Issues
Problem: SQLite database locked
# Close all processes accessing database
pkill -f "node src"
# Clear locks
npm run clear-locks
# If persists, delete and rebuild
rm data/page-cache.db
npm run index all
Problem: Want to revert to JSON cache
# Edit .env file:
USE_JSON_CACHE=true
PAGE_CACHE_PATH=./data/page-cache.json
# Restart services
npm run web
Getting Help
- Check logs: Look for error messages in terminal output
- Run diagnostics:
npm run statsandnpm run analytics - Validate setup:
npm testto run test suite - Check documentation: See
docs/folder for detailed guides - GitHub Issues: Report bugs at repository issues page
Common Error Messages
| Error | Solution |
|---|---|
ECONNREFUSED |
Ollama not running - start with ollama serve |
Item already exists |
Use FETCH_BATCH_SIZE=1 in .env |
Lock held by another process |
Run npm run clear-locks |
No such table: locks |
Normal on first run - table created automatically |
404 Not Found |
Documentation URL changed - run npm run rebuild |
ENOENT: no such file |
Create data directories: mkdir -p data/{vectors,html} |
🤝 Contributing
Contributions welcome! This project started during Hack Week 25.
See docs/CONTRIBUTING.md for guidelines.
📄 License
See LICENSE file for details.
🎯 Use Cases
- DevOps Engineers: Quickly find deployment and configuration info
- System Administrators: Navigate SUSE Linux documentation efficiently
- Kubernetes Users: Get instant answers about K3s and Rancher
- Technical Writers: Research and cross-reference documentation
- Support Teams: Find solutions faster with semantic search
🔗 Resources
Platform & Tools
Documentation Sources
- SUSE Documentation
- Rancher Documentation
- K3s Documentation
- RKE2 Documentation
- Longhorn Documentation
- Harvester Documentation
- NeuVector Documentation
- Kubewarden Documentation
Built with ❤️ for Hack Week 25.
Установка Docs Navigator SUSE Edition
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/mso-docs/Docs-Navigator-MCP-SUSE-EditionFAQ
Docs Navigator SUSE Edition MCP бесплатный?
Да, Docs Navigator SUSE Edition MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Docs Navigator SUSE Edition?
Нет, Docs Navigator SUSE Edition работает без API-ключей и переменных окружения.
Docs Navigator SUSE Edition — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Docs Navigator SUSE Edition в Claude Desktop, Claude Code или Cursor?
Открой Docs Navigator SUSE Edition на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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