kollabor 0.4.23

A terminal AI chat where everything has hooks

Kollabor

A terminal AI chat where everything has hooks. Every action -- user input, API calls, responses, tool use, rendering -- triggers hooks that plugins can intercept and modify. Use any LLM provider, build custom plugins, automate with pipe mode.

brew install kollaborai/tap/kollabor   # macOS
kollab                                  # start chatting

Why Kollabor

Most terminal AI tools are closed boxes. Kollabor is an open pipeline -- every stage is a hook you can tap into.

• Hook everything -- intercept user input, transform API requests, post-process responses, modify tool calls
• Plugin system -- drop a Python file in plugins/, it auto-discovers and loads
• Any provider -- OpenAI, Anthropic, Google, Azure, OpenRouter, Ollama, LM Studio, or any OpenAI-compatible endpoint
• OAuth login -- use your ChatGPT subscription directly with kollab --login openai
• MCP support -- Model Context Protocol for tool integration
• Pipe mode -- echo "query" | kollab -p for scripting and automation
• Agent system -- multi-step task execution with tool calling
• Slash commands -- /profile, /save, /terminal, /permissions, and more

Install

brew install kollaborai/tap/kollabor        # macOS (recommended)

curl -sS https://raw.githubusercontent.com/kollaborai/kollabor-cli/main/install.sh | bash  # cross-platform

Or manually: uv tool install kollabor / pipx install kollabor / pip install kollabor

Quick Start

Kollabor auto-detects your API keys from standard environment variables:

Environment Variable	Provider	Notes
ANTHROPIC_API_KEY	Anthropic	Claude models
OPENAI_API_KEY	OpenAI	GPT models
GEMINI_API_KEY	Google	Gemini models
OPENROUTER_API_KEY	OpenRouter	300+ models from any provider

export ANTHROPIC_API_KEY=sk-ant-...
kollab

That's it. No config files needed.

OpenAI OAuth (ChatGPT subscription)

Use your existing ChatGPT Plus/Pro account -- no API key needed:

kollab --login openai

Opens your browser, you authorize, and you're in. Uses the Responses API with your subscription quota.

Custom Profiles

For more control, create named profiles with env vars following the pattern KOLLABOR_{NAME}_{FIELD}:

# Local LLM via Ollama
KOLLABOR_LOCAL_PROVIDER=custom
KOLLABOR_LOCAL_BASE_URL=http://localhost:11434/v1
KOLLABOR_LOCAL_MODEL=llama3.1

kollab --profile local

Use /profile interactively to list, switch, and create profiles. See FEATURES.md for all configuration options.

Pipe Mode

kollab "What is the capital of France?"        # direct query
echo "Explain this code" | kollab -p           # from stdin
cat document.txt | kollab -p                   # from file
kollab --timeout 5min "Complex analysis task"  # with timeout

Providers

Provider	Type	How to Connect
Anthropic	Native	ANTHROPIC_API_KEY
OpenAI	Native	OPENAI_API_KEY or kollab --login openai
Google Gemini	Native	GEMINI_API_KEY
Azure OpenAI	Native	KOLLABOR_AZURE_* env vars
OpenRouter	Gateway	OPENROUTER_API_KEY (300+ models)
Ollama	Custom	KOLLABOR_LOCAL_BASE_URL=http://localhost:11434/v1
LM Studio	Custom	KOLLABOR_LMSTUDIO_BASE_URL=http://localhost:1234/v1
Any OpenAI-compatible	Custom	KOLLABOR_{NAME}_BASE_URL=...

Hooks & Plugins

Every stage of the pipeline is hookable:

user input → pre_user_input → pre_api_request → [LLM API] → post_api_response → pre_message_display → output
                                                    ↓
                                              pre_tool_use → [tool execution] → post_tool_use

Write a plugin:

from kollabor_plugins import BasePlugin
from kollabor_events import EventType, HookPriority

class MyPlugin(BasePlugin):
    def register_hooks(self):
        self.event_bus.register_hook(
            EventType.PRE_API_REQUEST,
            self.on_request,
            priority=HookPriority.NORMAL
        )

    async def on_request(self, context):
        # inject custom headers, modify messages, add tools, whatever
        context["headers"]["X-Custom"] = "value"
        return context

Drop it in plugins/ and it loads automatically. Plugins can register slash commands, add status bar widgets, merge config, and hook into 30+ event types.

Slash Commands

Command	Description
/profile	List, switch, create LLM profiles
/save	Save conversation (markdown, jsonl, clipboard)
/terminal	Manage tmux sessions
/permissions	Configure tool approval modes
/login	OAuth login (OpenAI)
/mcp	Manage MCP servers
/resume	Resume a previous conversation
/help	Show all available commands

Type / in the app to see the full command menu with 20+ commands.

Architecture

Kollabor is a monorepo. Each package is independently versioned and installable.

Package	What it does
kollabor-ai	LLM providers, profiles, OAuth, streaming
kollabor-agent	Tool execution, MCP, permissions
kollabor-tui	Terminal UI, rendering, design system
kollabor-events	Event bus, hook registry
kollabor-config	Configuration system
kollabor-plugins	Plugin framework, SDK
kollabor-engine	Web UI backend

The kollabor/ directory is a thin orchestration layer that wires the packages together.

.
├── kollabor/                  # Orchestration (app lifecycle, CLI, commands)
├── packages/                  # Independent packages (see table above)
├── plugins/                   # Plugin implementations
├── tests/                     # Test suite
└── main.py                    # Entry point

Development

git clone https://github.com/kollaborai/kollabor-cli.git
cd kollabor-cli
pip install -e ".[dev]"
python main.py

python tests/run_tests.py                    # all tests
python -m black kollabor/ plugins/ tests/    # format
python -m mypy kollabor/ plugins/            # type check

See CLAUDE.md for architecture details, coding standards, and contribution guidelines.

Links

• Quick Start Guide
• Feature Reference
• Plugin Development
• Bug Tracker

License

MIT