* feat: migrate container configuration from env vars to YAML config files
- Replace environment variable-based configuration with structured YAML config files
- Add Pydantic models for type-safe configuration management in cubbi_init.py
- Update container.py to generate /cubbi/config.yaml and mount into containers
- Simplify goose plugin to extract provider from default model format
- Remove complex environment variable handling in favor of direct config access
- Maintain backward compatibility while enabling cleaner plugin architecture
* feat: optimize goose plugin to only pass required API key for selected model
- Update goose plugin to set only the API key for the provider of the selected model
- Add selective API key configuration for anthropic, openai, google, and openrouter
- Update README.md with comprehensive automated testing documentation
- Add litellm/gpt-oss:120b to test.sh model matrix (now 5 images × 4 models = 20 tests)
- Include single prompt command syntax for each tool in the documentation
* feat: add comprehensive integration tests with pytest parametrization
- Create tests/test_integration.py with parametrized tests for 5 images × 4 models (20 combinations)
- Add pytest configuration to exclude integration tests by default
- Add integration marker for selective test running
- Include help command tests and image availability tests
- Document test usage in tests/README_integration.md
Integration tests cover:
- goose, aider, claudecode, opencode, crush images
- anthropic/claude-sonnet-4-20250514, openai/gpt-4o, openrouter/openai/gpt-4o, litellm/gpt-oss:120b models
- Proper command syntax for each tool
- Success validation with exit codes and completion markers
Usage:
- pytest (regular tests only)
- pytest -m integration (integration tests only)
- pytest -m integration -k "goose" (specific image)
* feat: update OpenCode plugin with perfect multi-provider configuration
- Add global STANDARD_PROVIDERS constant for maintainability
- Support custom providers (with baseURL) vs standard providers
- Custom providers: include npm package, name, baseURL, apiKey, models
- Standard providers: include only apiKey and empty models
- Use direct API key values from cubbi config instead of env vars
- Only add default model to the provider that matches the default model
- Use @ai-sdk/openai-compatible for OpenAI-compatible providers
- Preserve model names without transformation
- All providers get required empty models{} section per OpenCode spec
This ensures OpenCode can properly recognize and use both native
providers (anthropic, openai, google, openrouter) and custom
providers (litellm, etc.) with correct configuration format.
* refactor: model is now a combination of provider/model
* feat: add separate integration test for Claude Code without model config
Claude Code is Anthropic-specific and doesn't require model selection like other tools.
Created dedicated test that verifies basic functionality without model preselection.
* feat: update Claude Code and Crush plugins to use new config system
- Claude Code plugin now uses cubbi_config.providers to get Anthropic API key
- Crush plugin updated to use cubbi_config.providers for provider configuration
- Both plugins maintain backwards compatibility with environment variables
- Consistent plugin structure across all cubbi images
* feat: add environments_to_forward support for images
- Add environments_to_forward field to ImageConfig and Image models
- Update container creation logic to forward specified environment variables from host
- Add environments_to_forward to claudecode cubbi_image.yaml to ensure Anthropic API key is always available
- Claude Code now gets required environment variables regardless of model selection
- This ensures Claude Code works properly even when other models are specified
Fixes the issue where Claude Code couldn't access Anthropic API key when using different model configurations.
* refactor: remove unused environment field from cubbi_image.yaml files
The 'environment' field was loaded but never processed at runtime.
Only 'environments_to_forward' is actually used to pass environment
variables from host to container.
Cleaned up configuration files by removing:
- 72 lines from aider/cubbi_image.yaml
- 42 lines from claudecode/cubbi_image.yaml
- 28 lines from crush/cubbi_image.yaml
- 16 lines from goose/cubbi_image.yaml
- Empty environment: [] from opencode/cubbi_image.yaml
This makes the configuration files cleaner and only contains
fields that are actually used by the system.
* feat: implement environment variable forwarding for aider
Updates aider to automatically receive all relevant environment variables
from the host, similar to how opencode works.
Changes:
- Added environments_to_forward field to aider/cubbi_image.yaml with
comprehensive list of API keys, configuration, and proxy variables
- Updated aider_plugin.py to use cubbi_config system for provider/model setup
- Environment variables now forwarded automatically during container creation
- Maintains backward compatibility with legacy environment variables
Environment variables forwarded:
- API Keys: OPENAI_API_KEY, ANTHROPIC_API_KEY, DEEPSEEK_API_KEY, etc.
- Configuration: AIDER_MODEL, GIT_* variables, HTTP_PROXY, etc.
- Timezone: TZ for proper log timestamps
Tested: All aider tests pass, environment variables confirmed forwarded.
* refactor: remove unused volumes and init fields from cubbi_image.yaml files
Both 'volumes' and 'init' fields were loaded but never processed at runtime.
These were incomplete implementations that didn't affect container behavior.
Removed from all 5 images:
- volumes: List with mountPath: /app (incomplete, missing host paths)
- init: pre_command and command fields (unused during container creation)
The cubbi_image.yaml files now only contain fields that are actually used:
- Basic metadata (name, description, version, maintainer, image)
- persistent_configs (working functionality)
- environments_to_forward (working functionality where present)
This makes the configuration files cleaner and eliminates confusion
about what functionality is actually implemented.
* refactor: remove unused ImageInit and VolumeMount models
These models were only referenced in the Image model definition but
never used at runtime since we removed all init: and volumes: fields
from cubbi_image.yaml files.
Removed:
- VolumeMount class (mountPath, description fields)
- ImageInit class (pre_command, command fields)
- init: Optional[ImageInit] field from Image model
- volumes: List[VolumeMount] field from Image model
The Image model now only contains fields that are actually used:
- Basic metadata (name, description, version, maintainer, image)
- environment (loaded but unused - kept for future cleanup)
- persistent_configs (working functionality)
- environments_to_forward (working functionality)
This makes the data model cleaner and eliminates dead code.
* feat: add interactive configuration command
Adds `cubbi configure` command for interactive setup of LLM providers
and models through a user-friendly questionnaire interface.
New features:
- Interactive provider configuration (OpenAI, Anthropic, OpenRouter, etc.)
- API key management with environment variable references
- Model selection with provider/model format validation
- Default settings configuration (image, ports, volumes, etc.)
- Added questionary dependency for interactive prompts
Changes:
- Added cubbi/configure.py with full interactive configuration logic
- Added configure command to cubbi/cli.py
- Updated uv.lock with questionary and prompt-toolkit dependencies
Usage: `cubbi configure`
* refactor: update integration tests for current functionality
Updates integration tests to reflect current cubbi functionality:
test_integration.py:
- Simplified image list (removed crush temporarily)
- Updated model list with current supported models
- Removed outdated help command tests that were timing out
- Simplified claudecode test to basic functionality test
- Updated command templates for current tool versions
test_integration_docker.py:
- Cleaned up container management tests
- Fixed formatting and improved readability
- Updated assertion formatting for better error messages
These changes align the tests with the current state of the codebase
and remove tests that were causing timeouts or failures.
* fix: fix temporary file chmod
Cubbi - Container Tool
Cubbi is a command-line tool for managing ephemeral containers that run AI tools and development environments, with support for MCP servers. It supports Aider, Crush, Claude Code, Goose, Opencode.
🚀 Quick Reference
cubbi session create- Create a new sessioncubbix- Shortcut forcubbi session createcubbix .- Mount the current directorycubbix /path/to/dir- Mount a specific directory
📋 Requirements
📥 Installation
# Via uv
uv tool install cubbi
# Without installation
# (meaning all commands below must be prefixed with `uvx`)
uvx cubbi
Then compile your first image:
cubbi image build goose
cubbi image build opencode
cubbi image build crush
For Developers
If you are looking to contribute to the development, you will need to use uv as well:
git clone https://github.com/monadical-sas/cubbi
cd cubbi
uv tool install --with-editable . .
# You'll have cubbi and cubbix executable files in your PATH, pointing to the local installation.
📚 Basic Usage
# Show help message (displays available commands)
cubbi
# Create a new session with the default image (using cubbix alias)
cubbix
# Create a session and run an initial command before the shell starts
cubbix --run "ls -l"
# Create a session, run a command, and exit (no shell prompt)
cubbix --run "ls -l" --no-shell
# List all active sessions
cubbi session list
# Connect to a specific session
cubbi session connect SESSION_ID
# Close a session when done
cubbi session close SESSION_ID
# Close a session quickly (kill instead of graceful stop)
cubbi session close SESSION_ID --kill
# Close all sessions at once
cubbi session close --all
# Close all sessions quickly
cubbi session close --all --kill
# Create a session with a specific image
cubbix --image goose
cubbix --image opencode
cubbix --image crush
# Create a session with environment variables
cubbix -e VAR1=value1 -e VAR2=value2
# Mount custom volumes (similar to Docker's -v flag)
cubbix -v /local/path:/container/path
cubbix -v ~/data:/data -v ./configs:/etc/app/config
# Mount a local directory (current directory or specific path)
cubbix .
cubbix /path/to/project
# Forward ports from container to host
cubbix --port 8000 # Forward port 8000
cubbix --port 8000,3000,5173 # Forward multiple ports (comma-separated)
cubbix --port 8000 --port 3000 # Forward multiple ports (repeated flag)
# Connect to external Docker networks
cubbix --network teamnet --network dbnet
# Restrict network access to specific domains
cubbix --domains github.com --domains "api.example.com:443"
# Connect to MCP servers for extended capabilities
cubbix --mcp github --mcp jira
# Clone a Git repository
cubbix https://github.com/username/repo
# Using the cubbix shortcut (equivalent to cubbi session create)
cubbix # Creates a session without mounting anything
cubbix . # Mounts the current directory
cubbix /path/to/project # Mounts the specified directory
cubbix https://github.com/username/repo # Clones the repository
# Shorthand with MCP servers
cubbix https://github.com/username/repo --mcp github
# Shorthand with an initial command
cubbix . --run "apt-get update && apt-get install -y my-package"
# Execute a command and exit without starting a shell
cubbix . --run "python script.py" --no-shell
# Enable SSH server in the container
cubbix --ssh
🖼️ Image Management
Cubbi includes an image management system that allows you to build, manage, and use Docker images for different AI tools
Supported Images
| Image Name | Langtrace Support | Single Prompt Command |
|---|---|---|
| goose | yes | goose run -t 'prompt' --no-session --quiet |
| opencode | no | opencode run -m MODEL 'prompt' |
| claudecode | no | claude -p 'prompt' |
| aider | no | aider --message 'prompt' --yes-always --no-fancy-input |
| crush | no | crush run 'prompt' |
Automated Testing:
Each image can be tested with single prompt commands using different models:
# Test a single image with a specific model
cubbix -i goose -m anthropic/claude-sonnet-4-20250514 --no-connect --no-shell --run "goose run -t 'What is 2+2?' --no-session --quiet"
# Test aider with non-interactive flags
cubbix -i aider -m openai/gpt-4o --no-connect --no-shell --run "aider --message 'What is 2+2?' --yes-always --no-fancy-input --no-check-update"
# Test claude-code (note: binary name is 'claude', not 'claude-code')
cubbix -i claudecode -m anthropic/claude-sonnet-4-20250514 --no-connect --no-shell --run "claude -p 'What is 2+2?'"
# Test opencode with model specification
cubbix -i opencode -m anthropic/claude-sonnet-4-20250514 --no-connect --no-shell --run "opencode run -m anthropic/claude-sonnet-4-20250514 'What is 2+2?'"
# Test crush
cubbix -i crush -m anthropic/claude-sonnet-4-20250514 --no-connect --no-shell --run "crush run 'What is 2+2?'"
# Run comprehensive test suite (requires test.sh script)
./test.sh # Tests all images with multiple models: anthropic/claude-sonnet-4-20250514, openai/gpt-4o, openrouter/openai/gpt-4o, litellm/gpt-oss:120b
# List available images
cubbi image list
# Get detailed information about an image
cubbi image info goose
cubbi image info opencode
cubbi image info crush
# Build an image
cubbi image build goose
cubbi image build opencode
cubbi image build crush
Images are defined in the cubbi/images/ directory, with each subdirectory containing:
Dockerfile: Docker image definitionentrypoint.sh: Container entrypoint scriptcubbi-init.sh: Standardized initialization scriptcubbi_image.yaml: Image metadata and configurationREADME.md: Image documentation
Cubbi automatically discovers and loads image definitions from the YAML files.
## Development
```bash
# Run the tests
uv run -m pytest
# Run linting
uvx ruff check .
# Format code
uvx ruff format .
⚙️ Configuration
Cubbi supports user-specific configuration via a YAML file located at ~/.config/cubbi/config.yaml. This allows you to set default values and configure service credentials.
Managing Configuration
# View all configuration
cubbi config list
# Get a specific configuration value
cubbi config get langfuse.url
# Set configuration values
cubbi config set langfuse.url "https://cloud.langfuse.com"
cubbi config set langfuse.public_key "pk-lf-..."
cubbi config set langfuse.secret_key "sk-lf-..."
# Set API keys for various services
cubbi config set openai.api_key "sk-..."
cubbi config set anthropic.api_key "sk-ant-..."
# Reset configuration to defaults
cubbi config reset
Default Networks Configuration
You can configure default networks that will be applied to every new session:
# List default networks
cubbi config network list
# Add a network to defaults
cubbi config network add teamnet
# Remove a network from defaults
cubbi config network remove teamnet
Default Volumes Configuration
You can configure default volumes that will be automatically mounted in every new session:
# List default volumes
cubbi config volume list
# Add a volume to defaults
cubbi config volume add /local/path:/container/path
# Remove a volume from defaults (will prompt if multiple matches found)
cubbi config volume remove /local/path
Default volumes will be combined with any volumes specified using the -v flag when creating a session.
Default Ports Configuration
You can configure default ports that will be automatically forwarded in every new session:
# List default ports
cubbi config port list
# Add a single port to defaults
cubbi config port add 8000
# Add multiple ports to defaults (comma-separated)
cubbi config port add 8000,3000,5173
# Remove a port from defaults
cubbi config port remove 8000
Default ports will be combined with any ports specified using the --port flag when creating a session.
Default MCP Servers Configuration
You can configure default MCP servers that sessions will automatically connect to:
# List default MCP servers
cubbi config mcp list
# Add an MCP server to defaults
cubbi config mcp add github
# Remove an MCP server from defaults
cubbi config mcp remove github
When adding new MCP servers, they are added to defaults by default. Use the --no-default flag to prevent this:
cubbi mcp add github -e GITHUB_PERSONAL_ACCESS_TOKEN=xxxx github mcp/github --no-default
When creating sessions, if no MCP server is specified with --mcp, the default MCP servers will be used automatically.
External Network Connectivity
Cubbi containers can connect to external Docker networks, allowing them to communicate with other services in those networks:
# Create a session connected to external networks
cubbi session create --network teamnet --network dbnet
Important: Networks must be "attachable" to be joined by Cubbi containers. Here's how to create attachable networks:
# Create an attachable network with Docker
docker network create --driver bridge --attachable teamnet
# Example docker-compose.yml with attachable network
# docker-compose.yml
version: '3'
services:
web:
image: nginx
networks:
- teamnet
networks:
teamnet:
driver: bridge
attachable: true # This is required for Cubbi containers to connect
Service Credentials
Service credentials like API keys configured in ~/.config/cubbi/config.yaml are automatically passed to containers as environment variables:
| Config Setting | Environment Variable |
|---|---|
langfuse.url |
LANGFUSE_URL |
langfuse.public_key |
LANGFUSE_INIT_PROJECT_PUBLIC_KEY |
langfuse.secret_key |
LANGFUSE_INIT_PROJECT_SECRET_KEY |
openai.api_key |
OPENAI_API_KEY |
anthropic.api_key |
ANTHROPIC_API_KEY |
openrouter.api_key |
OPENROUTER_API_KEY |
google.api_key |
GOOGLE_API_KEY |
🌐 MCP Server Management
MCP (Model Control Protocol) servers provide tool-calling capabilities to AI models, enhancing their ability to interact with external services, databases, and systems. Cubbi supports multiple types of MCP servers:
- Remote HTTP SSE servers - External MCP servers accessed over HTTP
- Docker-based MCP servers - Local MCP servers running in Docker containers, with a SSE proxy for stdio-to-SSE conversion
Managing MCP Servers
# List all configured MCP servers and their status
cubbi mcp list
# View detailed status of an MCP server
cubbi mcp status github
# Start/stop/restart individual MCP servers
cubbi mcp start github
cubbi mcp stop github
cubbi mcp restart github
# Start all MCP servers at once
cubbi mcp start --all
# Stop and remove all MCP servers at once
cubbi mcp stop --all
# Run the MCP Inspector to visualize and interact with MCP servers
# It automatically joins all MCP networks for seamless DNS resolution
# Uses two ports: frontend UI (default: 5173) and backend API (default: 3000)
cubbi mcp inspector
# Run the MCP Inspector with custom ports
cubbi mcp inspector --client-port 6173 --server-port 6174
# Run the MCP Inspector in detached mode
cubbi mcp inspector --detach
# Stop the MCP Inspector
cubbi mcp inspector --stop
# View MCP server logs
cubbi mcp logs github
# Remove an MCP server configuration
cubbi mcp remove github
Adding MCP Servers
Cubbi supports different types of MCP servers:
# Example of docker-based MCP server
cubbi mcp add fetch mcp/fetch
cubbi mcp add github -e GITHUB_PERSONAL_ACCESS_TOKEN=xxxx github mcp/github
# Example of SSE-based MCP server
cubbi mcp add myserver https://myssemcp.com
Using MCP Servers with Sessions
MCP servers can be attached to sessions when they are created:
# Create a session with a single MCP server
cubbi session create --mcp github
# Create a session with multiple MCP servers
cubbi session create --mcp github --mcp jira
MCP servers are persistent and can be shared between sessions. They continue running even when sessions are closed, allowing for efficient reuse across multiple sessions.
📜 License
Cubbi is licensed under the MIT License.