No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by vishalsachdev · MCP Server · ★ 258
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is canvas-mcp safe to install? View the security audit →
Canvas MCP Server MCP server for Canvas LMS with 92 tools and 8 agent skills. Works with Claude Desktop, Cursor, Codex, Windsurf, and 40+ other agents. For AI Agents Canvas MCP provides 92 tools for interacting with Canvas LMS. Tools are organized by user type: Student Tools (click to expand) | getmype
| Stars | 258 |
| Forks | 88 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 73.187126853551/100 |
| Open Issues | 13 |
| Last Updated | 2026-09-23 |
| Created | 2025-02-28 |
| Platforms | claude-code, codex, mcp, python |
| Est. Tokens | ~19k |
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canvas-mcp is Canvas LMS MCP server — up to 102 tools and 8 agent skills for students & educators. Works with Claude, Cursor, Codex, and 40+ agents.. It is categorized as a MCP Server with 258 GitHub stars.
canvas-mcp is primarily written in Python. It covers topics such as agent-skills, skills-sh.
You can find installation instructions and usage details in the canvas-mcp GitHub repository at github.com/vishalsachdev/canvas-mcp. The project has 258 stars and 88 forks, indicating an active community.
canvas-mcp is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to canvas-mcp on Agent Skills Hub include marketing-skills, AIPex, AgentChat. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: