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Docs Navigator MCP - SUSE Edition

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Docs Navigator MCP - SUSE Edition

Docs Navigator MCP - SUSE Edition

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

Related MCP server: Dedalus MCP Documentation Server

🌟 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:

  1. 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

  2. Advanced Analytics & Queries

    • npm run analytics - Comprehensive cache health reports

    • npm run query-cache - Filter by source, status, date range

    • Cache efficiency metrics, stale page detection, automated recommendations

    • By-source breakdowns showing indexed/total ratios

  3. Concurrent Indexing Safety

    • Table-based locking prevents race conditions

    • 30-minute lock timeout with automatic expiration

    • npm run clear-locks for manual lock cleanup

    • Safe to run multiple indexing processes simultaneously

  4. 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

  5. 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-sqlite to convert JSON cache

  • New users: SQLite is default, no action needed

  • See docs/SQLITE_MIGRATION.md for details

🚀 Quick Start

Prerequisites

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

  1. Configure Claude Desktop (see docs/INSTALL.md)

  2. 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

  1. Indexing: Docs → Fetch → Parse → Chunk → Embed → Store in Vectra + Cache

  2. Searching: Query → Embed → Vector Search → Retrieve Docs → Return Results

  3. 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

  1. Check logs: Look for error messages in terminal output

  2. Run diagnostics: npm run stats and npm run analytics

  3. Validate setup: npm test to run test suite

  4. Check documentation: See docs/ folder for detailed guides

  5. 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

Built with ❤️ for Hack Week 25.

Install Server
A
license - permissive license
A
quality
D
maintenance

How are these scores calculated?

Maintenance

–Maintainers
–Response time
–Release cycle
–Releases (12mo)
Commit activity

Resources

Tools

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