Generate a prioritized study plan for today or the next N days based on upcoming deadlines.
AI agents call get_study_plan 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 queries and synthesizes existing academic data (assignments, deadlines, grades) to produce a prioritized plan. It is a read operation with no side effects—it retrieves information and presents it in organized form, similar to 'get_assignments', 'get_grades', and 'get_study_summary' which are also read tools on this server.
From the tool's definition Tool generates and retrieves a study plan based on existing data ('upcoming deadlines'). The verb 'Generate' in this context means synthesizing information from assignments and grades the student already has access to, not creating new data in the system.
Documented attack patterns abuse exactly the kind of access get_study_plan 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_study_plan:
{
"version": "1",
"default": "deny",
"tools": {
"get_study_plan": {}
}
}get_study_plan is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Generate a prioritized study plan for today or the next N days based on upcoming deadlines. 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_study_plan: 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_study_plan 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_study_plan 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_study_plan. 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_study_plan 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.
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8 Shiori MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.