List your upcoming assignments. Optionally filter by course or status.
AI agents call get_assignments to retrieve information from Shiori MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool only retrieves and lists data about assignments without modifying, deleting, or executing anything. It is purely informational, making it a Read category tool with low severity since exposure poses minimal risk—an AI agent using this tool would only gain visibility into assignment information already available to the authenticated user.
From the tool's definition Tool name is 'get_assignments' and description states 'List your upcoming assignments' with optional filtering. This is a retrieval operation with no side effects.
Documented attack patterns abuse exactly the kind of access get_assignments gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Shiori MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for get_assignments:
{
"version": "1",
"default": "deny",
"tools": {
"get_assignments": {}
}
}get_assignments is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
Free to start. No card required.
List your upcoming assignments. Optionally filter by course or status. It is categorised as a Read tool in the Shiori MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Shiori MCP Server MCP server in PolicyLayer and add a rule for get_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 Shiori MCP Server. Nothing to install.
get_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 get_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 get_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.
get_assignments is provided by the Shiori MCP Server MCP server (kaorii-ako/shiori-v1). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Shiori MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
8 Shiori MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.