The demo

The announcement post includes this demo video:

I recorded the video against the new agent.datasette.io live demo instance, which runs Datasette Agent against example databases including the classic global-power-plants by WRI, and a copy of the Datasette backup of my blog.

The live demo runs on Gemini 3.1 Flash-Lite – it’s cheap, fast and has no trouble writing SQLite queries.

A question I asked in the demo was:

When did Simon most recently see a pelican?

Which ran this SQL query:

SELECT
  title, commentary, created
FROM
  blog_beat
WHERE
  beat_type = 'sighting'
  AND (title LIKE '%pelican%' OR commentary LIKE '%pelican%')
ORDER BY
  created DESC
LIMIT
  5

And replied:

The most recent sighting of a pelican by Simon was recorded on May 20, 2026.

The observation included a California Brown Pelican, along with a Common Loon, Canada Goose, Striped Shore Crab, and a California Sea Lion.

That sighting on my blog, and the Markdown export of the full conversation transcript.

The plugins

My favorite feature of Datasette Agent is that it’s extensible using plugins. We’ve shipped three plugins so far:

• datasette-agent-charts, shown in the video, adds charts to Datasette Agent, powered by Observable Plot.
• datasette-agent-openai-imagegen adds an image generation tool to Datasette Agent using ChatGPT Images 2.0.
• datasette-agent-sprites provides tools for executing code in a Fly Sprites persistent sandbox.

Building plugins is really fun. I have a bunch more prototypes that aren’t quite alpha-quality yet. Claude Code and OpenAI Codex are both proving excellent at writing plugins – just point them at a checkout of the datasette-agent repo for reference and tell them what you want to build!

Runging it against local models

I’ve also been having fun running the new plugin against local models. Here’s a uv one-liner to run the plugin against gemma-4-26b-a4b in LM Studio on a Mac:

uvx --prerelease=allow \
  --with datasette-agent --with llm-lmstudio \
  datasette --internal internal.db --root \
  -s plugins.datasette-llm.default_model lmstudio/google/gemma-4-26b-a4b \
  data.db

Datasette Agent needs reliable tool calls and the ability for a model to produce SQL queries that run against SQLite. The open weight models released in the past six months are increasingly able to handle that.

What’s next?

Datasette Agent opens up so many opportunities for the LLM and Datasette ecosystem in general.

It’s already informed the major LLM 0.32a0 refactor which I’m nearly ready to roll into a stable release, maybe with some additional “LLM agent” abstractions extracte from Datasette Agent itself.

I’ve been exploring my own take on the Claude Artifacts, which is shaping up nicely as a plugin.

I’m excited to use Datasette Agent to build my own Claw – a personal AI assistant built around data imported from different parts of my digital life, which is a neat excuse to revisit my older Dogsheep family of tools.

We’ll also be rolling out Datasette Agent for users of Datasette Cloud.

Join our Discord channel if you’d like to talk about the project.

Key Takeaways

• Datasette Agent is a new extensible AI assistant for Datasette.
• We’ve shipped three plugins: datasette-agent-charts, datasette-agent-openai-imagegen, and datasette-agent-sprites.
• The plugin can run against local models like Gemini 3.1 Flash-Lite for efficient tool calls.
• Datasette Agent is paving the way for further development in the LLM and Datasette ecosystem, including a potential “LLM agent” abstraction.