CanvasPilot
Provides tools for interacting with the Canvas LMS API, enabling AI agents to manage courses, assignments, modules, pages, files, discussions, announcements, quizzes, submissions, inbox, and calendar events.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@CanvasPilotWhat assignments are due this week for my Canvas courses?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
CanvasPilot
Agentic Canvas LMS tools for LLMs — an MCP server + CLI that talks to Canvas's real REST API using the session your browser already has.
Most Canvas MCPs need a Personal Access Token. Many schools disable student PATs and hide Canvas behind SSO/MFA. CanvasPilot solves that with a stay-open session broker: you log in once in a real browser (Playwright, persistent profile), then every tool call rides that authenticated session — headless, for as long as the cookies live.
Same architecture as OpenCLI-style web agents (persistent browser session → site's real HTTP/JSON API), purpose-built for Canvas.
Features
Auth that works at real schools — session broker (SSO/MFA, no PAT needed) or classic
CANVAS_API_TOKENHeadless after one headed login —
session start --headlessreuses the saved profileFull REST surface — courses, assignments, modules, pages, files, discussions, announcements, planner, inbox, calendar, activity stream, submissions, and quizzes (list/questions/submissions/start/complete)
Agent-shaped digests —
assignment_brief(cleaned prompt + rubric),sync_summary(courses + upcoming),submission_statusFixture mode — offline dict backend for tests and CI; no Canvas required
33 MCP tools, one stdio server, zero config beyond
CANVAS_BASE_URL
Related MCP server: Canvas MCP
Install
pip install "canvaspilot[browser]" # or: pip install -e ".[browser]" from a checkout
playwright install chromiumRequires Python 3.11+.
Try it offline first
From an installed package or an editable source checkout:
python -m canvaspilot.offline_demo
# Optional: save to a NEW path (existing files are protected)
python -m canvaspilot.offline_demo --out synthetic-review.jsonThis exercises the high-level course and assignment-brief API on two explicitly synthetic courses. It strips prompt markup, preserves a missing due date as unknown, and returns readable JSON. No Canvas account, browser, token, session broker, model call, submission, or runtime network connection is needed. The example rejects writes and missing fixture routes instead of falling back to live access. Installing package dependencies requires network access separately.
This is a small, inspectable behavior demonstration, not evidence of live
pagination, working school authentication, or student outcomes. The tests in
tests/test_offline_demo.py protect these boundaries.
Quick start
export CANVAS_BASE_URL=https://<school>.instructure.com
# 1) Log in once (headed — finish SSO/MFA in the window), leave the broker running
canvaspilot session start
# 2) Later: restart headless on the same saved profile
canvaspilot session start --headless
# 3) Use it
canvaspilot whoami
canvaspilot courses
canvaspilot sync
canvaspilot brief <course_id> <assignment_id>With a PAT instead:
export CANVAS_API_TOKEN=... # broker not needed
canvaspilot coursesMCP server
canvaspilot mcp # stdioCursor / Claude Desktop / any MCP client:
{
"mcpServers": {
"canvas": {
"command": "canvaspilot",
"args": ["mcp"],
"env": { "CANVAS_BASE_URL": "https://<school>.instructure.com" }
}
}
}Tools exposed (all prefixed canvas_):
Area | Tools |
Identity |
|
Courses |
|
Assignments |
|
Discussions |
|
Quizzes |
|
Inbox / Calendar |
|
Full REST |
|
Programmatic API bundle: from canvaspilot.bundle import make_api, tool_inventory.
Auth modes
Mode | How | When |
session (default) | Playwright persistent profile + local broker on | School disables student PATs / SSO+MFA |
token |
| School allows PATs |
fixture |
| Tests, offline demos |
The broker only listens on loopback. Cookies never leave the Playwright profile directory; the MCP/CLI process never sees them — it asks the broker to make the request.
Configuration
Env | Default | Purpose |
|
| Your school's Canvas host |
| — | PAT (skips the broker) |
|
| Playwright persistent profile dir |
|
| Broker port |
|
| Output dir for |
Session broker commands
canvaspilot session start [--headless] [--base-url URL] [--profile DIR] [--port N]
canvaspilot session status
canvaspilot session stopScripts
scripts/readonly_sweep.py— live read-only smoke across the whole tool surface (needs a running broker)scripts/inventory_pass.py— per-course inventory: tabs, LTI/external tools, modules, third-party mentions
Development
pip install -e ".[dev]"
pytestTests run entirely in fixture mode.
Responsible use
CanvasPilot gives an agent the same access you have — including submitting assignments and starting quiz attempts. Write tools are clearly named; wire approval gates in your agent if you don't want autonomous submits. Follow your institution's academic integrity policy.
Origin
Extracted from the Suite monorepo (packages/canvaspilot), where it's synced via git subtree.
License
MIT
Maintainer
Jacob Metoyer — software and research tooling. Upstream and collaborator credit are retained.
This server cannot be deployed
Maintenance
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