CoCalc features

Keep people, AI agents, and project work together with notebooks, terminals, documents, software environments, collaboration, and history in persistent Linux projects.

• CPU, RAM, and GPU Compute for Research

  Explore research compute in CoCalc: CPU and RAM requirements, GPU workloads, remote Jupyter kernels, storage, and CLI inspection. Follow the documented setup and operating limits.

• Online Jupyter Notebooks

  Run collaborative Jupyter notebooks with cell chat, TimeTravel history, course workflows, and AI agent tools. Select a local or remote kernel with the language and packages your analysis needs.

• Online LaTeX Editor

  Write LaTeX online with collaboration, PDF preview, source synchronization, anchored discussions and edit history. Use SageTeX, PythonTeX and Knitr when their tools are installed in the project.

• Online Linux Terminal

  Use a hosted Linux terminal beside project files, notebooks, and collaborators. Reconnect to live shell sessions while the project runtime remains running.

• Online Linux Environment

  Use a hosted Linux environment with collaborative editors and terminals, project storage, SSH, and web apps. Choose an image and check its software and storage policies.

• Run Linux Graphical Applications Online

  Stream Wayland and X11 application windows from a Linux project with graphical support. Share a live display, use browser clipboard permissions and PipeWire audio, and choose compatible launchers.

• Online Software Environments

  Choose an available image for a hosted CoCalc project, from a lean base to a scientific stack. Check included software, customize persistent storage, and record versions for reruns.

• AI Agents

  Use integrated Codex near files, notebooks, terminals, screenshots, patches, review notes, and live notebook state, or run other agents as terminal tools.

• Whiteboard & Slides

  Use collaborative whiteboards for math, diagrams and Jupyter cells. Run Tree follows a rooted code-cell tree; TimeTravel reviews document history rather than restoring live kernel state.

• Teaching a Course

  Organize assignments, distribute files, collect work, and grade notebooks or other project files with a workflow built for technical courses, labs, and training environments.

• Online Python Environment

  Use Python online with Jupyter notebooks, scripts, terminals, and web apps. Select and verify the environment used by each tool; use compatible hosted GPU resources where available.

• R Statistical Software Online

  Use R online in a collaborative project. Choose an image with the R kernel, IDE, and document tools needed for notebooks, RMarkdown, Quarto, knitr, or scripts.

• Run Julia Online

  Run Julia online in a collaborative CoCalc project: the Julia image with its Jupyter kernel, Pluto reactive notebooks, VS Code in the browser, package environments that live with your files, and .jl scripts in a real Linux terminal.

• Use SageMath Online

  Use a hosted Sage image for collaborative notebooks, the sage command line and teaching. SageTeX needs matching TeX tools; long computations also need a running project runtime.

• Run GNU Octave Online

  Use an available hosted Octave image for notebooks, .m files, terminals and collaboration. Check package requirements, installation locations and configured backup coverage.

• HTTP API

  Use the CoCalc HTTP API for automation, integration, and provisioning workflows without depending on the web UI.

• CoCalc vs AI Agent Sandboxes

  Compare CoCalc's persistent shared projects with API-first AI agent sandboxes for collaboration, review, durable project work, and deployment.