Docker Explorer

# Docker MCP Server Project ## Project Overview This project aims to create a Model Context Protocol (MCP) server that provides tools and resources for interacting with Docker and container registries. Similar to how GitHub's API allows searching and interacting with repositories, this MCP server will enable AI assistants to search for, analyze, and interact with Docker images, containers, and related resources. ## Core Functionality ### Tools 1. **search_images** - Search for Docker images across registries - Parameters: query, registry (optional), limit - Returns: List of matching images with metadata 2. **search_tags** - Search for specific tags of Docker images - Parameters: image_name, tag_pattern - Returns: List of matching tags with metadata 3. **search_users** - Search for Docker Hub users/organizations - Parameters: username, limit - Returns: List of matching users/organizations 4. **get_image_details** - Get metadata and layer information for a specific image - Parameters: image_name, tag - Returns: Detailed image information including layers, size, creation date 5. **search_dockerfiles** - Search for Dockerfiles across public repositories - Parameters: query, limit - Returns: List of Dockerfiles with content and metadata 6. **get_comments** - Get comments on a Docker image - Parameters: image_name - Returns: List of comments with author and timestamp 7. **add_comment** - Add a comment to a Docker image - Parameters: image_name, comment_text, user_token - Returns: Confirmation of comment addition 8. **analyze_dockerfile** - Analyze a Dockerfile for best practices and security issues - Parameters: dockerfile_content - Returns: Analysis report with recommendations 9. **compare_images** - Compare two Docker images for differences - Parameters: image1_name, image1_tag, image2_name, image2_tag - Returns: Comparison report highlighting differences ### Resources 1. **docker://images/{query}** - Get information about Docker images matching a query 2. **docker://image/{name}/{tag}** - Get detailed information about a specific image and tag 3. **docker://user/{username}** - Get information about a Docker Hub user/organization 4. **docker://dockerfile/{repo}/{path}** - Get the content of a specific Dockerfile ## Technical Implementation ### API Integration 1. **Docker Registry API v2** - For basic image operations and metadata retrieval - Documentation: https://docs.docker.com/registry/spec/api/ 2. **Docker Hub API** - For user/organization information and social features - Documentation: https://docs.docker.com/docker-hub/api/latest/ 3. **Custom Indexing System** - For Dockerfiles (similar to how GitHub indexes code) - May require a separate service to crawl and index public Dockerfiles ### Authentication - Implement OAuth 2.0 for protected operations - Support for Docker Hub authentication tokens - Rate limiting to prevent abuse ### Data Storage - Cache frequently accessed data to improve performance - Consider using a vector database for semantic search capabilities - Store metadata in a structured database for efficient querying ## Development Roadmap ### Phase 1: Core Functionality 1. Set up basic MCP server structure 2. Implement Docker Registry API integration 3. Create basic search_images and get_image_details tools 4. Add resource endpoints for images and tags ### Phase 2: Enhanced Features 1. Add Docker Hub API integration 2. Implement user search and social features 3. Create Dockerfile search and analysis tools 4. Add authentication for protected operations ### Phase 3: Advanced Features 1. Implement semantic search for Dockerfiles and images 2. Add image comparison functionality 3. Create visualization tools for image layers 4. Implement caching and performance optimizations ## Potential Challenges 1. **API Rate Limiting**: Docker Hub and Registry APIs have rate limits that may affect heavy usage 2. **Authentication Handling**: Securely managing user credentials for authenticated operations 3. **Dockerfile Indexing**: Creating an efficient system to index and search Dockerfiles 4. **Performance**: Ensuring fast response times for search operations across large datasets ## Future Extensions 1. **Container Runtime Integration**: Add tools to interact with running containers 2. **Vulnerability Scanning**: Integrate with security scanning tools to check images for vulnerabilities 3. **Build Automation**: Allow building images from Dockerfiles 4. **Deployment Integration**: Connect with Kubernetes or Docker Swarm for deployment operations