marimo and marimo pair
Reactive Python notebook as a .py file; marimo pair lets Claude Code or Codex act inside the live kernel and read values back.
marimo
- Maker: marimo Inc. (Akshay Agrawal, Myles Scolnick), acquired by CoreWeave (announced 30 October 2025)
- URL: https://marimo.io and https://github.com/marimo-team/marimo
- Status (10 October 2026): Apache-2.0, 23.1k stars, release 0.25.1 on 1 October 2026, pushed
daily. CoreWeave said it stays open source.
marimo pair, an agent skill for driving a live notebook, launched in 2026 (repo created February 2026, Apache-2.0, 426 stars, last push September 2026); its underlyingmarimo._code_modeAPI is marked private and unstable.
What it is
A reactive Python notebook stored as a plain .py file. Cells form a dependency graph, so running
or editing one reruns its dependents and deletes stale state; notebooks can also run as scripts or
be served as apps with UI elements (sliders, tables, forms).
The problem it’s solving
Jupyter’s hidden state and out-of-order execution make notebooks irreproducible and hard to share. More recently: coding agents’ file and shell tools are bad at stateful data work, where the interesting values live in memory between steps.
Its path / bet
A notebook that is both a reproducible program and an interactive document. The 2026 bet is that agents should “use notebooks the way people do”: run code in the live kernel, inspect results, edit cells, and keep the useful work, while the person watches and edits the same notebook.
How it works (concretely)
- Static analysis of each cell’s definitions and references gives the dependency graph.
marimo edit nb.py --mcpexposes read-only MCP tools (inspect cells, data, errors).marimo pair(install withnpx skills add marimo-team/marimo-pair) gives Claude Code, Codex or any skills-capable harness a CLI that executes Python in the live kernel (with notebook variables in scope; “the call returns the resulting values and errors directly”) and a small API to add, edit and delete cells. After edits, marimo reports each cell as clean, errored or broken upstream. The team moved here after finding read-only MCP plus file edits too slow and too fixed.
Strengths
- The nearest thing in the landscape to fictty’s loop: an agent and a person share one live, stateful surface; the agent writes to it and reads exact values back.
- Reactive, reproducible, plain-file format; agents can diff and review it.
- Strong momentum and now a well-funded owner.
Weaknesses / limits
- It’s a notebook: the UI is code cells and their outputs, in a browser. Fine for data work, not a general screen.
- The agent API is private and unstable by their own description.
- Ownership by a GPU cloud may pull priorities towards CoreWeave’s platform.
Relation to fictty
Watch; partial competitor for one use case. For “the agent explores data with me and shows me charts,” marimo pair is a strong answer today, and the person gets real Python and real plots. It doesn’t run in the terminal, isn’t a screen for non-data tasks, and the agent reads back values, not what the person sees. Its lesson matters more than its overlap.
Could fictty adopt it instead of building?
Not as a substitute: a browser notebook can’t be the screen inside a herdr pane over SSH. For data exploration specifically, a fictty user could reasonably be pointed at marimo. A fictty data source could read from a marimo app’s outputs, but that’s speculative.
What fictty should take from it
- Live state beats files for agent work. marimo found that read-only tools plus file edits were too slow and moved to letting the agent act in the live process. fictty already lets agents act on the live screen; keep that the primary path and treat files as save and load.
- Report health after a patch. marimo tells the agent which cells are clean, errored or broken upstream. A fictty patch should return the same: which nodes rendered, which data sources failed, which bindings are now empty.
- A skill is the distribution.
npx skills addis how marimo reaches Claude Code and Codex. fictty should ship a skill the same way.
Sources
- marimo-team/marimo and marimo-pair (GitHub API, 10 October 2026)
- marimo, marimo pair and Notebooks as a tool for agents (20 July 2026)
- marimo docs, MCP
- CoreWeave, CoreWeave acquires Marimo (30 October 2025); Simon Willison, link post
- Talk Python, episode 555 on marimo pair (July 2026)