Project settings get a new home, @ mentions, Trash, & smarter schedules

A new home for project settings

Project settings have moved, here's where to find what.

Before: project files, integrations, and the machine picker lived in the left side panel, always visible.

Now: they live in a panel on the right, which opens when you click Settings in the top right of the screen. The same panel includes a new Triggers section, which exposes ways to run a notebook automatically or remotely.

The goal is less clutter in the default view, so notebooks stay front and center.

Self-pausing schedules

Scheduled notebooks can now pause themselves after a configurable number of consecutive failures, instead of failing forever and burning compute. It's on by default when you create a new schedule.

EU-hosted OpenAI models for Enterprise

Enterprise customers can now use OpenAI models hosted in the EU, served through Azure's Sweden Central region. If your compliance requirements mean AI processing has to stay in the EU, this one's for you.

@ mentions in notebooks

You can now mention integrations and projects directly in text blocks. Type @ in a paragraph, list, or callout and a picker opens — with typeahead, so you can find the right resource fast.

• Project chips link straight to that project.
• If a mentioned resource gets removed, its chip shows in red.
• Every chip carries the resource ID, so AI agents know unambiguously which integration or project you're referring to.

Trash folder

When you accidentally delete a project, you no longer have to reach out to support. Just restore it from Trash.

API & MCP updates

• Duplicate notebooks programmatically — a new POST /notebooks/{notebookId}/duplicate endpoint in the v2 API, with a matching duplicate_notebook MCP tool.
• Link generation for agents — a new generate_project_url MCP tool lets agents generate URLs for Deepnote projects and notebooks, so they can hand you a link to what they've built.

MCP tools & controls, Git directory sync, pivot tables, & more

MCP updates: better controls and more tools

New MCP tools for integrations

MCP-connected agents can now manage integrations end-to-end with three new tools: create_integration, attach_integration, and detach_integration. An agent can now create an integration and wire it into a project without a human step in between.

Better MCP controls for workspace admins

You can now see every MCP OAuth grant issued for your workspace and revoke any of them from Settings > Security > MCP OAuth connections.

A new workspace setting on the same page turns external MCP client access on or off for the whole workspace.

New block type: pivot tables

You can now summarize and cross-tabulate data with a dedicated pivot table block. Just drop in rows, columns, values, and an aggregation; no code required. It's a focused first version, and we'll expand it based on how people use it.

Git Directory Sync

A new Git integration flow that syncs each notebook to its own .deepnote file, so a project's notebooks show up as separate files in your repo instead of being bundled into a single multi-notebook .deepnote file. Existing projects on the old bundled format get a built-in migration path. More improvements are on the way.

Watch this walkthrough for a quick look at how the migration and sync work.

Collapsible sections in notebooks

Headings in notebooks are now collapsible, so you can fold away the parts you're not working on and move through a long notebook far more easily.

Better agent context

The AI agent now has access to our documentation, so questions about setup, configuration, and product behavior come back grounded in the actual docs.

Pick your AI model

The AI model selector in your settings now offers more fine-grained selection of the latest publicly available models from OpenAI or Anthropic. You can also try Anthropic’s latest Sonnet 5 in Deepnote!

SQL blocks in R environments

SQL blocks now work in R-based environments (Deepnote iR with libs). Query any Deepnote integration from a SQL block, and results land in an R dataframe, the R equivalent of the pandas dataframe you'd get in a Python notebook. Downstream blocks (including DataFrame SQL) can consume it from there.

BigQuery OAuth in the VS Code extension

The Deepnote VS Code extension (v1.5.0) now supports OAuth-based BigQuery integrations, so each user signs in with their own Google account instead of sharing a service account. Short-lived tokens, MFA, and least-privilege access apply automatically.

Because the OAuth flow is proxied through Deepnote, the same integration config and redirect URLs work in both places: if you already use BigQuery OAuth in Deepnote Cloud, the integration carries over.

Install the latest version from the VS Marketplace or Open VSX.

Setup details in the docs.

Deepnote is now in OpenAI Codex

Codex now connects natively to your Deepnote workspace. The context your team has already built — notebooks, scheduled analyses, data apps, and integrations — is available to Codex directly, so any exploration starts from your real work.

Watch this demo, where we connect Codex to a live workspace and run a fraud detection project end to end — summarizing projects, serving a model, auto-running the card-cancellation workflow, and writing a new analysis back into Deepnote.

Codex connects via the Deepnote MCP and operates within your existing permissions: it can search for projects, read and run notebooks, write new ones, and inspect integrations.

Here's what that unlocks:

Your workspace as the context for every exploration

Most real questions cross team boundaries. Codex can now search and read across every project in your workspace, pulling from the marketing, sales, and product notebooks to compose a single answer across all three — built on how your team already defines and measures things.

Turn a Codex exploration into a published Deepnote app

An exploration doesn't have to end as a chat thread. Because Codex can write back to Deepnote, you can share its work as a notebook or a published app your team can open, rerun, and extend.

Build and refine real workflows

Codex can interact with individual blocks in your notebooks, so you build persistent, production-ready workflows instead of one-off queries — adding features to a model, tuning thresholds, or dropping in monitoring over a few targeted prompts.

Connect Deepnote to Codex

1. Open Codex
2. Select Plugins and find Deepnote
3. Click Enabled in Codex, then Connect
4. Follow the OAuth flow and select a workspace

Deepnote is live in the Codex data analytics plugin today. The Deepnote MCP and public API behind this connection open up a lot more opportunities — more on that soon!

Run snapshots, Git sync, & AI usage visibility

TL;DR

• Run snapshots - every notebook run now saves an immutable record of blocks, outputs, and execution metadata, so you can jump back to any past run in a click.
• Git sync - connect a Deepnote project to a Git repo and keep them in sync automatically.
• AI usage visibility - workspace admins can now see every AI action taken, who triggered it, and the tokens it used.

Run snapshots

Every notebook run now automatically saves an immutable snapshot — a frozen record of all blocks, outputs, and execution metadata from the moment the run finished. Open any past run from the Runs sidebar, your project logs, or the Logs & Analytics modal.

Scheduled notebook broke overnight? A teammate's run produced an unexpected number? Want to see what a chart looked like last Tuesday? Until now, you'd re-run and hope. Now you've got the full historical record one click away, so debugging, auditing, and reviewing someone else's work just gets easier.

Full details in the docs.

Git sync

You can now connect a Deepnote project to a Git repo and keep them in sync automatically. That means you can:

• Edit locally: take a project from Deepnote Cloud to your machine, work on it, and push changes back.
• Put notebooks in your Git flow: pull requests, code review, proper history.
• Actually review notebook diffs: the .deepnote format is human-readable, so changes are finally reviewable.

Full details in the docs.

AI usage visibility

Workspace admins can now see a full breakdown of AI activity in the AI settings page:

• Every AI action taken in the workspace.
• Which user triggered it, and from which notebook.
• Token usage per request, including cached tokens.

Polars support, PDF export & a cleaner notebook

TL;DR

• Polars support - Polars DataFrames are first-class citizens in data tables and charts.
• Export.ipynbor.deepnotefiles to PDF - turn any notebook into a PDF in a click, straight from the notebook menu.
• A cleaner notebook & workspace - better table of contents, nested bullets in text blocks, tidier project sidebar, friendlier empty state, and simpler folder defaults.

Polars support

Deepnote now treats Polars DataFrames as first-class citizens:

• They render in the interactive data table, with the same filtering and sorting you already get with pandas.
• They work in charts, including server-side aggregation for large datasets.

SQL blocks still return pandas DataFrames for now. If you'd like that to be configurable, let us know.

Export your.ipynbor.deepnotefile to PDF

You can now export any notebook, whether it’s as a .ipynb or a native .deepnote file, straight to PDF. Just pick **Export as →**choose PDF with code or PDF without code.

You'll find the full set of export options in the same place: .deepnote, PDF, .ipynb, and Project as.zip, in the project topbar menu and in the left sidebar.

Full details in the docs.

Cleaner notebook & workspace

• Better table of contents

The table of contents now behaves the same way in notebooks and apps, and it lives on the notebook itself instead of being tucked into the left sidebar. Small change, but the inconsistency had been bugging us for a while.

• Nested bullet points

You no longer need a markdown block to create nested bullet lists. Just hit Tab to indent and Shift + Tab to outdent, right in a text block.

• A simpler project sidebar

We removed the separate Terminals section from the project sidebar. Terminals are still there when you need them, just without the dedicated sidebar slot.

How many KitKats to run your AI?

Last week, 12T of KitKat products disappeared somewhere between Italy and Poland. Following a thorough internal investigation, we have reason to believe our Deepnote Agent was responsible.

In its defense, AI is an energy-intensive process, and 413,793 KitKat bars amount to fewer than one bar per Deepnote user.

To take full accountability, your AI usage in Deepnote is now measured and visible to your workspace admins. Both in KitKat bars, and USD ($).

To view the usage, head to Settings → AI.

You’ll find a new subsection detailing feature usage, models called (remember, you can always bring your own custom model if you’re on our enterprise tiers), and how much the run costs you. Alongside these, you’ll find the new metric: KitKats consumed. The conversion is based on actual energy-per-token estimates for each model, mapped to the caloric content of a standard 4-finger KitKat bar (210 kcal, or 878,640 joules).

A single Deepnote Agent session burns roughly 1/50th of a KitKat. Across 500,000 users, it adds up. A more detailed breakdown:

For folks who care about the dollar equivalent, we offer a separate measure:

On another note, we believe that AI energy consumption deserves more visibility, and that the best unit of measurement is one everyone understands. It’s a KitKat.

Take a break and review your org’s AI usage in your workspace’s AI settings.

Interoperability with more notebook formats

Convert more file formats to Deepnote projects and vice versa

The Deepnote convert CLI previously supported bi-directional conversion between Deepnote projects and Jupyter notebooks. Based on popular demand, we shipped bidirectional, lossless notebook conversions between Deepnote, Jupyter, Quarto, Percent, and Marimo.

We’ve also included a smarter CLI with automatic format detection and a new -- format flag to make the work more seamless. This helps increase interoperability across projects and reduce lock-in, in the true spirit of open-source!

That means you can move work both ways:

• Bring your previous projects back into Deepnote without losing momentum, and enjoy the extended functionality Deepnote offers!
• Convert a Deepnote project into any of the above notebook formats when you need to share, archive, or run elsewhere

You can now also export projects and notebooks directly from the VS Code extension.

We will continue working on .deepnote format portability to better integrate it with the ecosystem - let us know if you have any suggestions!

Git upgrades & GitLab support

Git integration updates

On our Git integration front, we’ve reworked the three core actions: pull, commit, and push. Everything got a more polished UI, plus a set of improvements that make day-to-day collaboration smoother.

Support for merge conflict resolution

Previously, pull only supported fast-forward updates, which meant it worked only when branches weren’t divergent. Now you can pull even when branches diverge, and if Git can’t resolve conflicts automatically, Deepnote will show a conflict resolution modal where you can keep either your local changes or the incoming changes.

Pull with stash

No need to commit local changes just to pull anymore, even if they touch files updated on the remote. Deepnote can pull with stash, and if conflicts occur (between your local-only commits and remote, or between the stash and remote), you can resolve them in the same conflict resolution flow.

Commit and push

The commit and push modal got a big refresh:

• Preview your changes in a clean diff editor
• Exclude files from the commit
• Switch to a new branch directly from the modal
• Get prompted to open a PR after a successful push

We’ve also included a set of smaller improvements, including a clearer branch selector (with more intuitive new-branch creation) and a one-click shortcut to open your repository on GitHub directly from the integration menu.

GitLab support in Git integration

GitLab is now fully supported in Deepnote’s Git integration in the Files section - not just for exports.

You can now:

• Connect GitLab repositories to folders
• Pull changes from the remote
• Commit and push local changes
• Switch between branches

One key difference compared to GitHub: for GitLab, Deepnote performs Git actions on your behalf, whereas GitHub uses Deepnote’s GitHub App. As a result, the setup flow is slightly different. Full instructions are available in the new GitLab integration documentation.

Python & SQL language servers in VS Code, & bring your own environment

Python & SQL language servers in the VS Code extension

The Deepnote VS Code extension now ships with Python and SQL language servers, which means your editor can actually understand your code and your schema.

What you get out of the box:

• Diagnostics
• Type hints and method signature info
• Autocomplete for functions and variables
• Autocomplete for table and column names, powered by your real database schema

This is included in the newly released extension version 1.3.0, along with the other improvements shipped before the holidays.

Bring your own virtual environment to the VS Code Extension

You can now use the Deepnote VS Code extension with both managed and existing (external) Python environments. The environment list now clearly shows the type, and the extension can detect and reuse virtual environments you already have (poetry, uv, conda, native venv) instead of forcing you to create a new one. This comes in handy if, for instance, you have a custom or opinionated way of installing dependencies. In case the Deepnote toolkit is missing, the extension will guide you through installing it directly into the selected environment with clear progress and logs. We also improved safety and reliability around environment migration, cleanup, and toolkit installation to avoid conflicts or accidental deletion.

Deepnote is now open-source

After seven years of building on the notebook, we're opening it up. Deepnote is now open-source under the Apache 2.0 license. That includes the new .deepnote format — a human-readable, project-based standard built for collaboration, multiple languages, and AI agents working alongside you. Your existing work comes with you: convert any .ipynb with npx @deepnote/convert and open it in VS Code, Cursor, Windsurf, or JupyterLab. Star us on GitHub and build on it with us.

Read more about why we built a new notebook format here.

Bring your own AI model & GitLab export & new admin powers

Bring your own AI model

Enterprise workspaces can now connect their own OpenAI-compatible endpoints to power Deepnote Agent - giving you full control over the AI provider behind your data analysis workflows.

This is especially valuable for organizations that need to:

• Meet compliance or regional data requirements with specific AI providers
• Leverage proprietary or fine-tuned models optimized for specific use cases
• Keep data within specific infrastructure boundaries

Setting it up is straightforward:

• Head to Settings & Members → AI tab and click Add model
• Provide your endpoint URL, model ID, and API key
• Set it as your workspace default, and Agent will use your custom model for all analysis tasks

Learn more about custom AI models

Export notebooks to GitLab

Great news for GitLab users - you can now export your notebooks directly to GitLab repositories, just like you've been able to with GitHub.

Whether you need to back up your work, maintain audit trails for compliance, or trigger automated pipelines, exporting to GitLab is now just a few clicks away:

• Open any project, click the Version history icon in the top right, then select Connect Git repository and choose GitLab (you'll connect your GitLab account if you haven't already)
• Pick your repository, specify the target branch and path, and choose whether to include outputs
• Export manually with the Commit & push button, or set up automatic exports whenever you create a new version

Check out the docs to get started with GitLab exports.

New admin powers

We've shipped a suite of new workspace settings that give admins more control over security and permissions - perfect for enterprise teams with strict governance requirements.

• Restrict email invites to your domain: Admins can now limit workspace and project invites to only email addresses matching the workspace owner's domain, preventing accidental external invites
• Disable incoming connections workspace-wide: Turn off the ability for project editors to enable incoming connections, giving admins full control over external access points
• Control private project creation: Disable the creation of new private projects in your workspace while keeping existing ones intact
• Set default permissions for public projects: Choose what permissions workspace members get on newly created public projects - from Full access down to View only

These controls give you the flexibility to create the right permission environment suited to your organization's specific security and collaboration needs.