get_all_upcoming_work
AI agents call get_all_upcoming_work to retrieve information from Canvas LMS MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool name follows the 'get_*' pattern characteristic of read operations that retrieve data without side effects. Despite the empty description, context from the server's purpose (managing coursework and tracking assignments) and all sibling tools being read-only queries strongly indicates this queries upcoming work items. No evidence of write, execute, delete, or financial operations.
From the tool's definition Tool name 'get_all_upcoming_work' indicates a retrieval operation. Sibling tools on the same server (get_assignment, get_course, get_discussion_entries, get_rubric, get_submission, list_announcements, list_assignments) are all read-only queries.
Attacks that exploit this kind of access
get_all_upcoming_work. It is categorised as a Read tool in the Canvas LMS MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Canvas LMS MCP Server MCP server in PolicyLayer and add a rule for get_all_upcoming_work: 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 LMS MCP Server. Nothing to install.
get_all_upcoming_work 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_all_upcoming_work 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_all_upcoming_work. 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_all_upcoming_work is provided by the Canvas LMS MCP Server MCP server (pranavkarthik10/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.
Teams ship this data inside their own products. See what a licence covers →