Fetch metadata for a single assignment (due date, points, rubric, submission types, etc).
AI agents call get-assignment 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.
This tool retrieves assignment metadata (due date, points, rubric, submission types) without creating, modifying, deleting, or executing any changes. It has no side effects and poses minimal security risk as it only queries existing data.
From the tool's definition Tool name 'get-assignment' and description 'Fetch metadata for a single assignment' clearly indicate data retrieval with no modification. The verb 'fetch' is explicitly associated with Read operations.
Documented attack patterns abuse exactly the kind of access get-assignment 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 get-assignment:
{
"version": "1",
"default": "deny",
"tools": {
"get-assignment": {}
}
}get-assignment is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Fetch metadata for a single assignment (due date, points, rubric, submission types, etc). 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 get-assignment: 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.
get-assignment 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 get-assignment 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 get-assignment. 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.
get-assignment is provided by the Canvas MCP Server MCP server (r-huijts/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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50 Canvas MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.