Personal AI Lab — Experimenting with AI agents in your terminal, as a Python library, or as a gateway service.
CLIver is an AI Agent research and experimentation project. It provides the building blocks to explore agent architectures — Re-Act loops, tool calling, skill activation, memory systems, and multi-agent orchestration — through a terminal CLI and an admin web UI.
A lab, not a product. CLIver is designed for tinkering. Swap models mid-conversation. Test how different system prompts change behavior. Add custom skills and tools to see what sticks.
Full-stack agent experimentation. Run interactively in the terminal, embed AgentCore as a Python library in your own experiments, or deploy as a gateway service with cron scheduling and messaging platform adapters.
pip install cliver
# Configure your LLM provider
cliver provider add --name deepseek --type openai \
--api-url https://api.deepseek.com --api-key "DEEPSEEK_API_KEY"
# Configure a model
cliver model add -n deepseek-v4-flash --provider deepseek
# Start experimenting
cliver "What can you help me with?"- Model-agnostic — OpenAI + Anthropic protocols, any provider, switch on the fly
- Built-in tools — file I/O, shell, web search, browser, memory, todo tracking, image generation
- Skills system — LLM-activated domain expertise following the Agent Skills spec
- Permission control — default, auto-edit, and YOLO modes with per-tool overrides
- Persistent memory — remembers preferences and context across sessions
- Gateway mode — daemon with cron scheduling, admin web UI, and messaging platform adapters
- Embeddable API —
AgentCore.chat()and.stream()for your own Python experiments
Full documentation at cliver-project.github.io/CLIver
git clone https://github.com/cliver-project/CLIver.git
cd CLIver
make init # Set up dev environment
make test # Run tests
make lint # Lint and format check
make format # Auto-fix lint/format issues
make docs-serve # Start docs website (hot reload)
make docs-build # Build docs to static files