AI agents use add_assignment to create or update resources in Shiori MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Shiori MCP Server environment.
The tool creates or modifies data reversibly by adding a new assignment record. It does not execute code, delete data irreversibly, or involve financial transactions. While a student could misuse this to add false assignments, the impact is limited to their own study system and can be corrected (Write category).
From the tool's definition Tool name is 'add_assignment' and description states 'Add a new assignment to Shiori' — this creates new data in the system.
Documented attack patterns abuse exactly the kind of access add_assignment 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 add_assignment:
{
"version": "1",
"default": "deny",
"tools": {
"add_assignment": {
"limits": [
{
"counter": "add_assignment_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}add_assignment stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
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Add a new assignment to Shiori. It is categorised as a Write tool in the Shiori MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Shiori MCP Server MCP server in PolicyLayer and add a rule for add_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 Shiori MCP Server. Nothing to install.
add_assignment is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the add_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 add_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.
add_assignment 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.