Where can I find the documentation?
Documentation is available online on GitHub Pages or offline by running `make docs` after installing dev dependencies.
@styada
基本情報
Trying to use mcp servers for setting up local rag
ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
An example implementation of a Python application applying Clean Architecture and SOLID principles, providing a template for building maintainable services. It includes out-of-the-box functionalities like FastAPI, Dramatiq, Socket.io, SQLAlchemy, and OpenTelemetry.
Create a GitHub repository using the template. Install uv and Docker, then use Docker commands like make containers, docker compose up dev-http, or Make commands like make install-dependencies and make dev-http. Run tests with make test or docker compose run --rm test.
Documentation is available online on GitHub Pages or offline by running `make docs` after installing dev dependencies.
You need to install `uv` and Docker. On macOS, `uv` can be installed with `brew install uv`; Docker can be downloaded from docker.com.
Yes, it includes authentication and Identity Provider using ORY Zero Trust architecture, and full observability with OpenTelemetry (Metrics, Traces, Logs).
It uses SQLAlchemy with the repository pattern and Alembic for database migrations, configured to support both sync and async engines.
It is an example implementation but includes production-like features such as CI/CD pipelines, authentication, observability, and a minimized Dockerfile for smaller production images.

Exact, shared memory for AI agents: a hierarchical database where totals always add up, every write is attributed to the agent and person behind it, and any figure traces back to its source file. Agents create databases,

Ask your Takibi Base collections anything; get answers with cited passages and a support score.

The official Semantic-UI-React integration

Shared memory for AI coding agents. Claude Code, Cursor and Codex read your project's decisions, lessons and tasks before they act.
Groundwork: company memory for your AI tools. Docs public. Source closed. Public proof needs no account.
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