Open-source Canvas LMS AI Agent
Canvas Pilot is an open-source Canvas LMS AI agent for students and AI power users who want recurring Canvas coursework to become a local-first, review-first workflow.
The problem
Canvas LMS stores assignments, modules, files, pages, and submissions, but many real coursework workflows repeat outside a single Canvas description. A course may always hide the real spec on an external site. Another course may always require the same reading annotation format. A third may always need the same draft, check, and report loop.
A generic AI agent can inspect Canvas every time, but the user still pays the coordination cost if the agent has to rediscover the same course pattern every week.
What Canvas Pilot adds
Canvas Pilot uses Canvas access as one input, then adds workflow memory, approval boundaries, per-assignment result files, and a final report. The core loop is:
scan Canvas -> approval plan -> student approval -> approved workflow -> review-ready output -> REPORT.md
The public repository ships a generic framework. Real course data, cookies, credentials, assignment inputs, drafts, and local overlays stay on the user's machine.
The open-source boundary
The open-source part is the workflow framework: scanning, planning, approval, dispatch, result files, reporting, hooks, and public-safe skill skeletons. Private course identifiers and user coursework do not belong in the public repo.
This is why Canvas Pilot is local-first rather than a hosted homework service. It is built for operators who can run local agents, inspect files, and decide what should or should not be submitted.
Related pages
Read Canvas Pilot vs Canvas MCP, the Canvas MCP workflow layer page, or the open-source GitHub repo.