AI agents call list_assignments to retrieve information from Canvas MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool performs a query operation to retrieve assignment data from Canvas LMS. It does not create, modify, delete, or execute any actions - it only reads and returns information. This is a straightforward Read category tool with low severity since unauthorized access to assignment listings poses minimal risk compared to modifications or deletions.
From the tool's definition Tool name is 'list_assignments' and description states 'List all assignments for a course' - this is a retrieval operation with no side effects.
Documented attack patterns abuse exactly the kind of access list_assignments gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Canvas MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for list_assignments:
{
"version": "1",
"default": "deny",
"tools": {
"list_assignments": {}
}
}list_assignments is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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List all assignments for a course. It is categorised as a Read tool in the Canvas MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Canvas MCP Server MCP server in PolicyLayer and add a rule for list_assignments: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Canvas MCP Server. Nothing to install.
list_assignments is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the list_assignments rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for list_assignments. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
list_assignments is provided by the Canvas MCP Server MCP server (plyght/canvas-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Canvas MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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30 Canvas MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.