exasol-quickstart 0.3.7

One command to try Exasol with AI add-ons (MCP Server + JSON Tables) — auto-selects the right setup for your OS (Windows / macOS / Linux).

exasol-quickstart

Run Exasol with AI in one command — a full Exasol analytics database, an LLM-ready MCP server, and JSON-native SQL, set up the right way for your operating system.

Get started in one line

pipx run exasol-quickstart

Pick the form that fits — try it (runs once, nothing installed) or keep it (installs the command for repeated use), with either pipx or uv:

	with pipx	with uv
Try it once	pipx run exasol-quickstart	uvx exasol-quickstart
Keep it	pipx install exasol-quickstart && exasol-quickstart	uv tool install exasol-quickstart && exasol-quickstart

Every form detects your OS, provisions Exasol the right way, and prints the endpoints. No flags, no multi-step setup.

What you get

exasol-quickstart  ->  three services on one shared network:

+----------------------+   +----------------------+   +----------------------+
|  Exasol  (database)  |   |  MCP server          |   |  JSON Tables         |
|  127.0.0.1:8563      |   |  :4896/mcp           |   |  JSON  ->  SQL       |
+----------------------+   +----------------------+   +----------------------+

Component	Endpoint	Purpose
Exasol (database)	127.0.0.1:8563 — user sys / password exasol	the Exasol SQL engine
MCP Server	http://127.0.0.1:4896/mcp	connect Claude / any MCP client to the database
JSON Tables	exasol-quickstart json-tables ...	ingest JSON and query it as SQL

Web UI: https://127.0.0.1:8443.

Requirements

The only universal prerequisite is Python 3.9+ with pipx:

python -m pip install --user pipx
python -m pipx ensurepath

From there, exasol-quickstart chooses how Exasol runs, per platform:

Operating system	How Exasol runs	Docker
Windows	Exasol Nano, in a container	required (no native Windows engine exists)
macOS (Apple Silicon)	Exasol Personal, in a native VM	not required (experimental)
Linux	Exasol Nano, in a container (native install planned)	required for now

The container path is fully tested today; the macOS native path is experimental and not yet validated end to end.

Usage

exasol-quickstart                      # full stack: database + MCP + JSON Tables
exasol-quickstart --no-json-tables     # database + MCP only
exasol-quickstart --dry-run            # print the plan, change nothing
exasol-quickstart --base <name>        # force a base: nano-docker | personal | nano-native
exasol-quickstart json-tables --help   # run the JSON Tables CLI

Ingest some JSON:

docker cp data.json exasol-quickstart-json-tables:/workspace/data.json
exasol-quickstart json-tables ingest-and-wrap --input /workspace/data.json --name demo

Stop and remove everything:

docker rm -f exasol-quickstart-db exasol-quickstart-mcp exasol-quickstart-json-tables

How it works

exasol-quickstart is a single front-door command that detects the platform and assembles the stack. With Docker, Exasol Nano, the official exasol/mcp-server image, and a JSON Tables sidecar run as containers on a shared network (tested end to end, including ingest). Without Docker, macOS uses Exasol Personal in a native VM and Linux uses a native Nano install (planned), with the add-ons as isolated host environments.

MCP Server and JSON Tables have incompatible pyexasol requirements, so each runs in isolation — a separate container or host environment — never a shared Python environment.

Links

• PyPI: https://pypi.org/project/exasol-quickstart/
• GitHub: https://github.com/krishna-exasol/exasol-quickstart

License

MIT