Runcell: AI Agent for Jupyter Notebooks | hokai.io
Runcell adds an AI agent inside JupyterLab that writes, runs, and debugs code from natural language. Free tier: 50 credits/month. Pro: $20/month with 500 credits.
Runcell is a JupyterLab extension and AI agent that writes, runs, and debugs Python code inside Jupyter notebooks from natural-language instructions. It reads actual notebook state including variable values and cell outputs, making it more accurate than general-purpose coding assistants for data science tasks. The free Hobby plan includes 50 credits/month; Pro costs $20/month for 500 credits and unlimited code completions. Works with JupyterLab 4.0 and newer only.
Pricing
Hobby (Free): 50 credits/month plus 50 bonus credits during beta. Pro: $20/month includes 500 credits/month and unlimited code completions.
Frequently Asked Questions
What is Runcell and what does it do?
Runcell is a JupyterLab extension and Python package that adds an AI agent directly inside Jupyter notebooks. It generates and executes Python code from natural-language instructions, reads actual cell outputs and DataFrame structures in memory, and operates in four modes: Autonomous Agent (full workflow automation), Reasoning Mode (step-by-step analysis), Interactive Learning (AI tutoring with live code), and Smart Edit (context-aware code assistance). It is designed specifically for data scientists and analysts who work daily in Jupyter.
How much does Runcell cost?
Runcell offers a free Hobby plan that includes 50 credits per month, plus 50 bonus credits during the beta period. The Pro plan costs $20 per month and includes 500 credits per month along with unlimited code completions and priority support. Credits are consumed per AI action, with complex Autonomous Agent sessions using more credits than simple chat edits. Credits do not roll over between months.
What are the main features of Runcell?
Runcell's four core modes are Autonomous Agent Mode (plans, writes, runs, and debugs complete analysis workflows), Reasoning Mode (step-by-step problem solving for complex code), Interactive Learning Mode (AI tutor with runnable code examples), and Smart Edit Mode (chat for targeted edits and chart generation). All modes read actual notebook state, including live variable values and DataFrame contents, giving them grounding that general coding assistants lack.
Is Runcell free to use?
Yes, Runcell has a free Hobby plan with 50 credits per month plus 50 bonus credits during the ongoing beta period. The free plan provides access to all four AI modes but with limited monthly credit allocation. For data scientists running daily analyses, the 50 credits per month are typically sufficient for lightweight weekly tasks but not for heavy multi-step Autonomous Agent workflows. Upgrading to Pro at $20/month unlocks 500 credits and unlimited code completions.
What are the best alternatives to Runcell?
For Jupyter users, the main alternatives are Jupyter AI (the official open-source extension), GitHub Copilot (available inside JupyterLab with limited notebook context), and AIMQ. For data scientists open to leaving Jupyter, Cursor and Windsurf offer stronger multi-file coding assistance in their own IDEs. Runcell differentiates itself from all of these by reading actual notebook state, making it the most Jupyter-native option, though Jupyter AI provides a fully free alternative for cost-sensitive teams.
Who is Runcell best for?
Runcell is best for data scientists who spend the majority of their working day in JupyterLab running exploratory analyses, cleaning datasets, and generating visualizations. It is also well-suited to academic researchers who want AI assistance within reproducible notebook workflows, and to Python learners who benefit from the Interactive Learning Mode's live code explanations. Runcell is not suitable for data engineers or ML engineers working primarily in Python scripts, VS Code notebooks, or Databricks, as it only integrates with JupyterLab 4.0 and newer.
Does Runcell have an API?
Runcell is installed as a Python package and JupyterLab extension via pip or conda, and does not currently expose a public REST API for external programmatic access. Integration is entirely within the JupyterLab interface using the Jupyter kernel and nbclient for execution. The extension communicates with JupyterLab's real-time collaboration layer (Jupyter RTC) to read and modify notebook state. For documentation on setup and configuration, visit docs.runcell.dev.