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Kagura AI

kagura-agent

CI Coverage License: Apache 2.0 Python 3.11+

A memory-backed autonomous AI agent. It combines a pluggable agentic brain, Kagura Memory Cloud, a Docker security membrane, and a Slack/Discord cockpit. Use it from the CLI with run, repl, serve, doctor, and setup.

The default brain is Claude through the Claude Agent SDK for Python. The optional kagura-brain backend adds Claude, Codex, and Ollama-compatible providers behind the same interface.

Status: alpha, package version 0.7.1. The v0.1–v0.7 pure-Python skeleton is implemented and tested with strict typing and at least 95% coverage. Live Docker, cloud credential, and chat-transport edges remain deployment-specific.

Why kagura-agent

  • Persistent memory: decisions, failures, and progress survive individual runs.
  • Real hands: filesystem, shell, Git, Docker, cloud APIs, and custom MCP tools.
  • Bounded autonomy: credentials, mounts, and egress are granted per task.
  • Operator control: long-running work can be launched, resumed, approved, or stopped from a CLI or chat cockpit.

Quickstart

You need Python 3.11 or newer, a Kagura Memory Cloud login, and a configured brain. The base package intentionally ships without a brain dependency.

python -m venv .venv
# Activate the virtual environment, then install the default brain:
pip install 'kagura-agent[claude]'

# Authenticate both required services:
kagura auth login
claude

# Verify the environment and run a task:
kagura-agent doctor
kagura-agent run "summarize the repository layout"

ANTHROPIC_API_KEY can replace the Claude subscription login. For the kagura-brain Claude/Codex/Ollama backend, chat transports, Docker mode, Windows activation, and first-run troubleshooting, see Getting started.

Main commands

Command Purpose
kagura-agent run "…" Run one task
kagura-agent repl Continue an interactive session
kagura-agent serve --transport slack Start the chat cockpit
kagura-agent doctor Check memory, brain, Docker, and provider readiness
kagura-agent setup transport Show transport setup guidance

Architecture at a glance

The session layer orchestrates tasks and checkpoints without depending on a specific model SDK. The selected brain owns its agentic tool loop; Kagura Memory Cloud provides durable context; the host-side membrane controls filesystem, network, and credential access.

kagura-agent architecture

The full rationale, provider boundary, capability model, security membrane, and cockpit protocol live in the design document.

Documentation

Document Contents
Documentation index Map of all project documentation
Getting started Installation, authentication, commands, bootstrap, troubleshooting
Design Scope, architecture, capabilities, security membrane, cockpit internals
Project status and scope Current boundary, roadmap, repository map, milestone coverage
Extending Custom MCP tools, egress, credential leasing, secret handling
Operations Incident response and credential rotation runbooks
Bootstrap evaluation Ranking evaluation and rollout gate
Legal notes Open terms-of-service and operator-responsibility questions
Contributing Development workflow and contribution guide
Security policy Supported versions and vulnerability reporting
Changelog Release history

Development

git clone https://github.com/kagura-ai/kagura-agent.git
cd kagura-agent
pip install -e '.[dev]'
pytest
mypy

See CONTRIBUTING.md for the full development workflow.

Related repositories

Repository Role
kagura-ai/kagura-engineer Independent coding-specialized sibling agent
kagura-ai/kagura-code-reviewer Review subagent used by kagura-engineer
kagura-ai/memory-cloud Persistent memory backbone and MCP server
kagura-ai/kagura-memory-python-sdk Trusted-host bootstrap SDK

License

Apache License 2.0 — © 2026 Kagura AI. See NOTICE for attribution.

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