Use this tool to retrieve all items within a specific module in a Canvas course. This tool returns a list of module item objects containing details like title, type, and URLs. Use this when you need to access specific learning materials, assignments, or other content within a module.
AI agents call get_module_items to retrieve information from Canvas MCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and lists module content from Canvas LMS without any capability to create, modify, delete, or execute operations. It is a straightforward data retrieval operation analogous to 'list' or 'get' operations. The blast radius of misuse is minimal—an agent could only access course materials that are already visible within the Canvas ecosystem. No side effects or irreversible actions are possible.
From the tool's definition Tool description states it 'retrieve[s] all items within a specific module' and 'returns a list of module item objects containing details'. The verbs 'retrieve' and 'returns' indicate query-only functionality with no data modification.
Attacks that exploit this kind of access
Use this tool to retrieve all items within a specific module in a Canvas course. This tool returns a list of module item objects containing details like title, type, and URLs. Use this when you need to access specific learning materials, assignments, or other content within a module. It is categorised as a Read tool in the Canvas MCP MCP Server, which means it retrieves data without modifying state.
Register the Canvas MCP server in PolicyLayer and add a rule for get_module_items: 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. Nothing to install.
get_module_items 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_module_items 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_module_items. 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_module_items is provided by the Canvas MCP server (noahjohannessen/canvas-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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