OMDB MCP Server
A Model Context Protocol (MCP) Server powered by Spring AI that provides access to the Open Movie Database (OMDB) API. This server uses Spring AI's native MCP Server support to allow AI assistants and other MCP clients to search for movies and retrieve detailed movie information.
Table of Contents
- OMDB MCP Server
Features
🎬 Movie Database Access
- Search Movies: Search for movies by title, year, and type
- Get Movie Details: Retrieve detailed information about a specific movie by title
- Get Movie by IMDB ID: Get detailed information using IMDB ID
- Rich Metadata: Access to ratings, cast, plot, awards, and more
⚡ Intelligent Caching System
- Automatic Caching: All OMDB API responses are automatically cached to reduce API calls
- Configurable TTL: Cache entries expire after 1 hour by default (configurable)
- Memory Efficient: Maximum cache size of 1000 entries with LRU eviction policy
- Performance Monitoring: Built-in cache statistics and management endpoints
- Rate Limit Protection: Helps stay within OMDB API usage limits and reduces costs
🔌 MCP Protocol Compliance
- MCP 2024-11-05: Fully implements the latest MCP specification
- HTTP JSON-RPC: Direct HTTP transport optimized for web service integration
- JSON-RPC 2.0: Standard protocol with proper error codes (-32700, -32600, -32601, -32602, -32603)
- Tool Discovery: Dynamic tool listing with JSON Schema validation
- Enhanced Schemas: Rich metadata, validation rules, and examples for better AI understanding
- Protocol Methods: Full support for initialize, ping, tools/list, tools/call, and notifications
🚀 Production Ready
- Docker Support: Multi-platform container images (AMD64/ARM64)
- Health Checks: Built-in monitoring and health endpoints
- Configuration: Environment-based configuration
- Logging: Structured logging with configurable levels
- Testing: Comprehensive test suite with coverage reporting
🔧 Developer Experience
- GitHub Actions: Complete CI/CD pipeline
- Automated Releases: Tagged releases with artifacts
- Security Scanning: Vulnerability detection and reporting
- OpenAPI Documentation: Interactive API documentation with Swagger UI
- Code Quality: Automated dependency updates and code analysis
🏗️ Architecture & Technology Stack
Technology Stack
- ☕ Java 24: Latest Java with modern features and performance improvements
- 🍃 Spring Boot 3.5.4: Production-ready application framework
- 🤖 Spring AI 1.0.0: Native MCP Server support with autoconfiguration
- ⚡ Spring WebFlux: Reactive programming with SSE transport for MCP communication
- 🗄️ Spring Cache + Caffeine: High-performance in-memory caching with automatic management
- 🐳 Docker: Containerized deployment with multi-stage builds
- 🧪 JUnit 5: Comprehensive testing framework with Spring Boot Test integration
- 📊 JaCoCo: Code coverage analysis
- 🔒 Spring Security: Security scanning and best practices
Architecture Overview
┌─────────────────┐
│ MCP Client │
│ (Claude Desktop)│
└─────────────────┘
│
┌──────┴──────┐
│ │
┌────────▼─────┐ ┌─────▼──────────┐
│ SSE │ │ HTTP REST │
│ Transport │ │ Controller │
│ (/sse) │ │ (Port 8081) │
└────────┬─────┘ └─────┬──────────┘
│ │
└──────┬──────┘
▼
┌─────────────────┐
│ Spring AI MCP │
│ Autoconfigured │
│ Function Beans │
└─────────────────┘
│
▼
┌─────────────────┐
│MovieSearchTools │◀─--┐
│ (Function Impl) │ │
└─────────────────┘ │
│ │
▼ │
┌─────────────────┐ │
│ OMDB Service │ │
│ (External API) │ │
└─────────────────┘ │
│ │
▼ │
┌─────────────────┐ ┌─────────────────┐ │
│ Cache Manager │ │ Caffeine Cache │ │
│ (Statistics) │ │ (In-Memory) │ │
└─────────────────┘ └─────────────────┘ │
│ ▲ │
│ │ │
▼ Cache Miss │
┌─────────────────┐ │ │
│ Cache Endpoints │ │ │
│ /cache/stats │ ▼ │
│ /cache/clear │ ┌─────────────────┐ │
└─────────────────┘ │ OMDB API │ │
│ (omdbapi.com) │ │
└─────────────────┘ │
│ │
└────────────--┘
Cache Hit
Key Components
- 🤖 Spring AI MCP: Autoconfigured MCP server with WebFlux SSE transport
- �️ MovieSearchTools: Service providing OMDB movie search functionality as Spring AI Function beans
- ⚙️ McpServerConfig: Configuration class registering Function beans for MCP tool discovery
- 🌐 OmdbService: OMDB API integration with reactive WebClient and intelligent caching
- ⚡ Cache Layer: Caffeine-based in-memory caching with configurable TTL and LRU eviction
- 📊 Cache Management: REST endpoints for cache statistics and management (/cache/*)
- � SSE Transport: Server-Sent Events endpoint (/sse) for real-time MCP communication
- 📋 Model Classes: Request/response records for strongly-typed Function interfaces
- ⚙️ Configuration: Spring AI MCP autoconfiguration via application.properties
Security Features
- 🔐 Non-root Docker user
- 🛡️ Automated vulnerability scanning
- 🚫 No sensitive data in images
- ✅ Health checks and monitoring
- 🔒 HTTPS support for external APIs
Prerequisites
- Java 24 or higher
- Maven 3.6 or higher
- OMDB API Key (free registration at http://www.omdbapi.com/apikey.aspx)
Quick Start
🐳 Using Docker (Recommended)
# Pull and run the latest Docker image
docker run -p 8081:8081 -e OMDB_API_KEY=your-api-key ghcr.io/tyrell/omdb-mcp-server:latest
📦 Using Pre-built JAR
- Download the latest JAR from Releases
- Run with your OMDB API key:
java -jar omdb-mcp-server-*.jar --omdb.api.key=your-api-key
🔨 Building from Source
-
Clone and build the project:
git clone https://github.com/tyrell/omdb-mcp-server cd omdb-mcp-server ./mvnw clean package -
Set your OMDB API key:
export OMDB_API_KEY=your-actual-api-key-here -
Run the server:
./mvnw spring-boot:run
The server will start on http://localhost:8081
📖 View API Documentation: Once running, access the interactive API documentation at http://localhost:8081/swagger-ui/index.html
🔧 Configuration
Environment Variables
OMDB_API_KEY: Your OMDB API key (required)SERVER_PORT: Server port (default: 8081)SPRING_AI_MCP_SERVER_NAME: MCP server name (default: "OMDB Movie Database Server")SPRING_AI_MCP_SERVER_VERSION: MCP server version (default: "0.2.0-SNAPSHOT")
Cache Configuration
The server includes intelligent caching to reduce OMDB API calls:
# Cache Configuration (default values shown)
cache.expire-after-write=1h # Cache TTL (Time To Live)
cache.maximum-size=1000 # Maximum number of cached entries
cache.record-stats=true # Enable cache statistics
Cache management endpoints:
GET /cache/stats- View cache performance statisticsDELETE /cache/clear- Clear all cachesDELETE /cache/clear/{cacheName}- Clear specific cache
Docker Compose
version: '3.8'
services:
omdb-mcp-server:
image: ghcr.io/tyrell/omdb-mcp-server:latest
ports:
- "8081:8081"
environment:
- OMDB_API_KEY=your-api-key-here
healthcheck:
test: ["CMD", "wget", "--no-verbose", "--tries=1", "--spider", "http://localhost:8081/actuator/health"]
interval: 30s
timeout: 3s
retries: 3
Spring AI MCP Server Configuration
For AI clients like Claude Desktop, use the Server-Sent Events (SSE) transport:
SSE Endpoint: http://localhost:8081/sse
Claude Desktop Configuration (claude_desktop_config.json):
{
"mcpServers": {
"omdb": {
"command": "java",
"args": ["-jar", "/path/to/omdb-mcp-server.jar"],
"env": {
"OMDB_API_KEY": "your-actual-api-key-here"
}
}
}
}
Alternative: Direct SSE Connection: If using a custom MCP client that supports SSE:
const eventSource = new EventSource('http://localhost:8081/sse');
eventSource.onmessage = function(event) {
// Handle MCP messages
const mcpMessage = JSON.parse(event.data);
};
Transport Mode:
- HTTP JSON-RPC: MCP protocol over HTTP at
/mcpendpoint on port 8081
MCP Tools
1. search_movies
Search for movies by title in the OMDB database.
Parameters:
title(required): Movie title to search foryear(optional): Year of releasetype(optional): Type of result (movie, series, or episode)
Example:
{
"jsonrpc": "2.0",
"id": "1",
"method": "tools/call",
"params": {
"name": "search_movies",
"arguments": {
"title": "The Matrix",
"year": "1999"
}
}
}
2. get_movie_details
Get detailed information about a specific movie by title.
Parameters:
title(required): Movie titleyear(optional): Year of releaseplot(optional): Plot length ("short" or "full", default: "full")
Example:
{
"jsonrpc": "2.0",
"id": "2",
"method": "tools/call",
"params": {
"name": "get_movie_details",
"arguments": {
"title": "The Shawshank Redemption",
"plot": "full"
}
}
}
3. get_movie_by_imdb_id
Get detailed information about a movie by IMDB ID.
Parameters:
imdbId(required): IMDB ID (e.g., "tt0111161")plot(optional): Plot length ("short" or "full", default: "full")
Example:
{
"jsonrpc": "2.0",
"id": "3",
"method": "tools/call",
"params": {
"name": "get_movie_by_imdb_id",
"arguments": {
"imdbId": "tt0111161"
}
}
}
MCP Protocol Implementation
This server implements the MCP 2024-11-05 specification using Spring AI's native MCP Server support with the following capabilities:
Supported Methods
- initialize: Server initialization and capability negotiation (handled by Spring AI)
- ping: Connection testing and keep-alive (handled by Spring AI)
- tools/list: Dynamic tool discovery via Function bean registration
- tools/call: Tool execution through Spring AI Function interface
- notifications/initialized: Client initialization completion (handled by Spring AI)
Spring AI Function Registration
Tools are automatically registered as Function beans and discovered by Spring AI:
@Configuration
public class McpServerConfig {
@Bean
public Function<SearchMoviesRequest, String> searchMovies(MovieSearchTools movieSearchTools) {
return movieSearchTools::searchMovies;
}
@Bean
public Function<GetMovieDetailsRequest, String> getMovieDetails(MovieSearchTools movieSearchTools) {
return movieSearchTools::getMovieDetails;
}
@Bean
public Function<GetMovieByImdbIdRequest, String> getMovieByImdbId(MovieSearchTools movieSearchTools) {
return movieSearchTools::getMovieByImdbId;
}
}
SSE Transport
Spring AI MCP Server uses Server-Sent Events for real-time communication:
- Endpoint:
GET /sse - Content-Type:
text/event-stream - Connection: Persistent bidirectional communication
List Tools
{
"jsonrpc": "2.0",
"id": "2",
"method": "tools/list"
}
Configuration
The server can be configured using environment variables or application.properties:
Core Configuration
# Server Configuration
server.port=8081
# OMDB API Configuration
omdb.api.url=https://www.omdbapi.com/
omdb.api.key=${OMDB_API_KEY:your-api-key-here}
# Spring AI MCP Server Configuration
spring.ai.mcp.server.enabled=true
spring.ai.mcp.server.name=OMDB Movie Database Server
spring.ai.mcp.server.version=0.2.0-SNAPSHOT
spring.ai.mcp.server.description=Spring AI MCP Server for searching and retrieving movie information from OMDB API
spring.ai.mcp.server.type=ASYNC
spring.ai.mcp.server.transport.type=SSE
# Cache Configuration
cache.expire-after-write=1h # Cache TTL (Time To Live)
cache.maximum-size=1000 # Maximum number of cached entries
cache.record-stats=true # Enable cache statistics
# Logging Configuration
logging.level.co.tyrell.omdb_mcp_server=INFO
logging.level.root=WARN
logging.level.org.springframework.cache=DEBUG # For cache debugging
logging.level.org.springframework.ai.mcp=DEBUG # For MCP debugging
# Actuator (Health Checks)
management.endpoints.web.exposure.include=health,info
management.endpoint.health.show-details=when-authorized
Advanced Configuration
# WebClient Configuration
spring.webflux.timeout=30s
spring.reactor.netty.pool.max-connections=100
# JVM Tuning (for production)
JAVA_OPTS=-Xmx512m -Xms256m -XX:+UseG1GC
🧪 Testing & Validation
Health Check
curl http://localhost:8081/actuator/health
Cache Performance Testing
Check cache statistics:
curl http://localhost:8081/cache/stats
Clear cache for testing:
# Clear all caches
curl -X DELETE http://localhost:8081/cache/clear
# Clear specific cache
curl -X DELETE http://localhost:8081/cache/clear/movieSearch
Test cache effectiveness:
-
Make an initial request (cache miss):
time curl -X POST http://localhost:8081/mcp \ -H "Content-Type: application/json" \ -d '{"jsonrpc":"2.0","id":"1","method":"tools/call","params":{"name":"search_movies","arguments":{"title":"The Matrix"}}}' -
Repeat the same request (cache hit - should be much faster):
time curl -X POST http://localhost:8081/mcp \ -H "Content-Type: application/json" \ -d '{"jsonrpc":"2.0","id":"2","method":"tools/call","params":{"name":"search_movies","arguments":{"title":"The Matrix"}}}' -
Check cache statistics to see hit/miss ratios:
curl http://localhost:8081/cache/stats
MCP Protocol Testing
Initialize the MCP connection:
curl -X POST http://localhost:8081/mcp \
-H "Content-Type: application/json" \
-d '{
"jsonrpc": "2.0",
"id": "1",
"method": "initialize",
"params": {
"protocolVersion": "2024-11-05",
"capabilities": {},
"clientInfo": {
"name": "test-client",
"version": "1.0.0"
}
}
}'
List available tools:
curl -X POST http://localhost:8081/mcp \
-H "Content-Type: application/json" \
-d '{
"jsonrpc": "2.0",
"id": "2",
"method": "tools/list"
}'
Search for movies:
curl -X POST http://localhost:8081/mcp \
-H "Content-Type: application/json" \
-d '{
"jsonrpc": "2.0",
"id": "3",
"method": "tools/call",
"params": {
"name": "search_movies",
"arguments": {
"title": "The Matrix",
"year": "1999"
}
}
}'
📋 For comprehensive testing approaches and alternatives to MCP Inspector, see MCP_TESTING_GUIDE.md
🔍 Development & Debugging
Run tests:
./mvnw test
Run cache-specific tests:
./mvnw test -Dtest="*Cache*"
Generate test coverage report:
./mvnw jacoco:report
# View report at target/site/jacoco/index.html
Build Docker image locally:
docker build -t omdb-mcp-server:local .
🚀 CI/CD & Deployment
This project includes comprehensive GitHub Actions workflows:
- 🔄 Continuous Integration: Automated testing, linting, and security scanning
- 📦 Build & Package: JAR and Docker image creation
- 🐳 Docker: Multi-platform container builds (AMD64/ARM64)
- 🏷️ Release: Automated releases with GitHub Releases and container registry
- 🔒 Security: Vulnerability scanning with Trivy
- 📈 Dependencies: Automated dependency updates
Deployment Options
-
GitHub Container Registry:
docker pull ghcr.io/tyrell/omdb-mcp-server:latest -
Manual JAR Deployment:
- Download from GitHub Releases
- Deploy on any Java 24+ environment
-
Kubernetes:
apiVersion: apps/v1 kind: Deployment metadata: name: omdb-mcp-server spec: replicas: 2 selector: matchLabels: app: omdb-mcp-server template: metadata: labels: app: omdb-mcp-server spec: containers: - name: omdb-mcp-server image: ghcr.io/tyrell/omdb-mcp-server:latest ports: - containerPort: 8081 env: - name: OMDB_API_KEY valueFrom: secretKeyRef: name: omdb-secret key: api-key
📖 OpenAPI Documentation
The OMDB MCP Server provides comprehensive OpenAPI documentation for both the MCP protocol endpoints and administrative endpoints.
Access Documentation
When the server is running, you can access the interactive API documentation at:
- Swagger UI: http://localhost:8081/swagger-ui/index.html
- OpenAPI JSON: http://localhost:8081/v3/api-docs
API Endpoints
MCP Protocol Endpoints
POST /mcp - Handle MCP requests (JSON-RPC 2.0)
- Purpose: Main endpoint for Model Context Protocol communication
- Content-Type: application/json
- Methods Supported:
initialize- Initialize MCP connectiontools/list- Get available toolstools/call- Execute tool operations
GET /mcp/health - Health check endpoint
- Purpose: Verify the MCP server is running
- Response: Plain text status message
Cache Management Endpoints
GET /cache/stats - Get cache statistics
- Purpose: Retrieve detailed cache performance metrics
- Response: JSON with hit rates, miss rates, and entry counts
DELETE /cache/clear - Clear all caches
- Purpose: Remove all cached entries from all caches
- Response: JSON success message
DELETE /cache/clear/{cacheName} - Clear specific cache
- Purpose: Remove all entries from the specified cache
- Parameters:
cacheName(path) - Name of the cache to clear
- Response: JSON success/error message
OpenAPI Specification
openapi: 3.0.1
info:
title: OMDB MCP Server API
description: |
A Model Context Protocol (MCP) Server that provides access to the Open Movie Database (OMDB) API.
This server allows AI assistants and other MCP clients to search for movies and retrieve detailed movie information.
## Features
- **Movie Search**: Search for movies by title, year, and type
- **Movie Details**: Get detailed information about specific movies
- **IMDB Integration**: Retrieve movies by IMDB ID
- **Intelligent Caching**: Automatic caching of OMDB API responses
- **MCP Compliance**: Full implementation of the Model Context Protocol 2024-11-05
## MCP Protocol
The server implements the JSON-RPC 2.0 based Model Context Protocol for communication with AI assistants.
Supported methods:
- `initialize`: Initialize the MCP connection
- `tools/list`: Get available tools
- `tools/call`: Execute tool operations
## Available Tools
- `search_movies`: Search for movies by title
- `get_movie_details`: Get detailed movie information by title
- `get_movie_by_imdb_id`: Get movie information by IMDB ID
contact:
name: OMDB MCP Server
url: https://github.com/tyrell/omdb-mcp-server
license:
name: MIT License
url: https://opensource.org/licenses/MIT
version: 1.0.0
servers:
- url: http://localhost:8080
description: Default server
paths:
/mcp:
post:
tags:
- MCP Controller
summary: Handle MCP Request
description: Processes Model Context Protocol requests including tool discovery and movie search operations
operationId: handleMcpRequest
requestBody:
description: MCP JSON-RPC 2.0 request
content:
application/json:
schema:
$ref: '#/components/schemas/McpRequest'
examples:
Initialize:
summary: Initialize MCP connection
value:
jsonrpc: "2.0"
id: "1"
method: initialize
params:
protocolVersion: "2024-11-05"
capabilities: {}
clientInfo:
name: example-client
version: 1.0.0
List Tools:
summary: Get available tools
value:
jsonrpc: "2.0"
id: "2"
method: tools/list
params: {}
Search Movies:
summary: Search for movies
value:
jsonrpc: "2.0"
id: "3"
method: tools/call
params:
name: search_movies
arguments:
title: The Matrix
year: "1999"
required: true
responses:
"200":
description: MCP response
content:
application/json:
schema:
$ref: '#/components/schemas/McpResponse'
examples:
Success Response:
summary: Successful MCP response
value:
jsonrpc: "2.0"
id: "3"
result:
content:
- type: text
text: |
🎬 The Matrix (1999)
Rating: R
Runtime: 136 min
Genre: Action, Sci-Fi
Director: Lana Wachowski, Lilly Wachowski
Cast: Keanu Reeves, Laurence Fishburne, Carrie-Anne Moss
IMDB Rating: 8.7/10
Plot: When a beautiful stranger leads computer hacker Neo to a forbidding underworld, he discovers the shocking truth--the life he knows is the elaborate deception of an evil cyber-intelligence.
/mcp/health:
get:
tags:
- MCP Controller
summary: Health Check
description: Simple health check endpoint to verify the MCP server is running
operationId: health
responses:
"200":
description: Server is healthy
content:
text/plain:
examples:
default:
value: MCP Server is running
/cache/stats:
get:
tags:
- Cache Controller
summary: Get Cache Statistics
description: Returns detailed statistics for all active caches including hit rates, miss rates, and entry counts
operationId: getCacheStats
responses:
"200":
description: Cache statistics retrieved successfully
content:
application/json:
examples:
default:
value:
omdbMovies:
size: 42
hitCount: 156
missCount: 48
hitRate: 0.764706
missRate: 0.235294
requestCount: 204
loadCount: 48
evictionCount: 0
/cache/clear:
delete:
tags:
- Cache Controller
summary: Clear All Caches
description: Removes all entries from all active caches
operationId: clearAllCaches
responses:
"200":
description: All caches cleared successfully
content:
application/json:
examples:
default:
value:
message: All caches cleared successfully
/cache/clear/{cacheName}:
delete:
tags:
- Cache Controller
summary: Clear Specific Cache
description: Removes all entries from the specified cache
operationId: clearCache
parameters:
- name: cacheName
in: path
description: Name of the cache to clear
required: true
schema:
type: string
responses:
"200":
description: Cache operation completed
content:
application/json:
examples:
Success:
summary: Cache cleared successfully
value:
message: Cache 'omdbMovies' cleared successfully
Not Found:
summary: Cache not found
value:
error: Cache 'nonexistent' not found
components:
schemas:
McpRequest:
type: object
properties:
jsonrpc:
type: string
description: JSON-RPC version
example: "2.0"
default: "2.0"
id:
type: string
description: Request identifier
example: "1"
method:
type: string
description: Method name
example: tools/call
enum:
- initialize
- tools/list
- tools/call
params:
type: object
additionalProperties:
type: object
description: Method parameters
example:
name: search_movies
arguments:
title: The Matrix
description: Model Context Protocol JSON-RPC 2.0 request
McpResponse:
type: object
properties:
jsonrpc:
type: string
description: JSON-RPC version
example: "2.0"
default: "2.0"
id:
type: string
description: Request identifier
example: "1"
result:
type: object
description: Response result (present on success)
error:
$ref: '#/components/schemas/McpError'
description: Model Context Protocol JSON-RPC 2.0 response
McpError:
type: object
properties:
code:
type: integer
format: int32
description: Error code
example: -32601
message:
type: string
description: Error message
example: Method not found
data:
type: object
description: Additional error data
description: MCP error details
Example Usage
Initialize MCP Connection
curl -X POST http://localhost:8080/mcp \
-H "Content-Type: application/json" \
-d '{
"jsonrpc": "2.0",
"id": "1",
"method": "initialize",
"params": {
"protocolVersion": "2024-11-05",
"capabilities": {},
"clientInfo": {
"name": "example-client",
"version": "1.0.0"
}
}
}'
Get Available Tools
curl -X POST http://localhost:8080/mcp \
-H "Content-Type: application/json" \
-d '{
"jsonrpc": "2.0",
"id": "2",
"method": "tools/list",
"params": {}
}'
Search for Movies
curl -X POST http://localhost:8080/mcp \
-H "Content-Type: application/json" \
-d '{
"jsonrpc": "2.0",
"id": "3",
"method": "tools/call",
"params": {
"name": "search_movies",
"arguments": {
"title": "The Matrix",
"year": "1999",
"type": "movie"
}
}
}'
API Response Format
All responses follow the MCP protocol format:
{
"jsonrpc": "2.0",
"id": "request-id",
"result": {
"content": [
{
"type": "text",
"text": "Formatted movie information..."
}
]
}
}
Error Handling
The server returns standard JSON-RPC error responses:
{
"jsonrpc": "2.0",
"id": "request-id",
"error": {
"code": -32602,
"message": "Invalid params",
"data": null
}
}
Common error codes:
-32700: Parse error-32600: Invalid request-32601: Method not found-32602: Invalid params-32603: Internal error
🤝 Contributing
We welcome contributions! Please see our Contributing Guide for details.
Development Setup
- Fork the repository
- Clone your fork:
git clone https://github.com/your-username/omdb-mcp-server cd omdb-mcp-server - Set up development environment:
# Install Java 24 and Maven ./mvnw clean compile export OMDB_API_KEY=your-test-api-key - Run tests:
./mvnw test - Make your changes and submit a PR
Code Style
- Follow Java conventions
- Write tests for new features
- Update documentation
- Ensure CI passes
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
🙏 Acknowledgments
- Open Movie Database (OMDB) for providing the movie data API
- Model Context Protocol for the protocol specification
- Spring Boot for the excellent framework
- All contributors who help improve this project
📞 Support
- 🐛 Bug Reports: GitHub Issues
- 💡 Feature Requests: GitHub Discussions
- 📖 Documentation: Project Wiki
- 🤖 LLM Integration: LLM_INTEGRATION_GUIDE.md - Detailed guide for AI assistant integration
- 🔒 Security Issues: See SECURITY.md
