Source Code:
hub/agents/python/docker/gaia_agent_docker/agent.pyComponent: DockerAgent - Intelligent Docker Containerization
Module:
gaia_agent_docker.agent
Inherits: MCPAgent
Model: Qwen3.5-35B-A3B-GGUF (default)Overview
DockerAgent helps developers containerize applications through natural language. It analyzes application structure, generates optimized Dockerfiles using LLM intelligence, and manages Docker image builds and container runs. Key Features:- Automatic application analysis (Python/Flask, Node/Express, etc.)
- LLM-generated Dockerfiles following best practices
- Docker build/run orchestration
- MCP server integration for external tool access
- Security: path validation
Requirements
Functional Requirements
-
Application Analysis
- Detect app type (Flask, Django, FastAPI, Express, React)
- Find entry points (app.py, server.js, etc.)
- Parse dependencies (requirements.txt, package.json)
- Suggest appropriate ports
-
Dockerfile Generation
- Use LLM to generate content based on analysis
- Follow best practices (layer caching, non-root users)
- Include copyright headers
- Support custom base images
-
Docker Operations
- Build images with tagging
- Run containers with port mapping
- Capture build/run output
- Report success/failure
-
MCP Integration
- Expose
dockerizetool via MCP - Accept absolute paths only
- Validate inputs
- Return structured results
- Expose
API Specification
DockerAgent Class
MCP Tool Definition
Implementation Details
Application Analysis
Dockerfile Generation (LLM)
System Prompt teaches LLM best practices:Security: Path Validation
Testing Requirements
Unit Tests
Dependencies
Usage Examples
Example 1: CLI Usage
Example 2: Python API
Example 3: MCP Integration
Related Specifications
- agent-base - Agent architecture
- mcp-server - MCP server system
- jira-agent - Similar agent pattern
DockerAgent Technical Specification