Update status for multiple sources in a single transaction.
AI agents use update_status to create or update resources in literateMCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your literateMCP environment.
This tool modifies the status field of source records in the literature database. It is reversible (status can be changed again), affects multiple records atomically, and is a standard write operation. It does not delete data (Destructive), execute arbitrary code (Execute), involve financial transactions (Financial), or retrieve data without side effects (Read).
From the tool's definition Tool name 'update_status' and description 'Update status for multiple sources in a single transaction' indicate modification of existing data records.
Documented attack patterns abuse exactly the kind of access update_status gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and literateMCP, and nothing reaches the server without passing your rules. This is the rule we recommend for update_status:
{
"version": "1",
"default": "deny",
"tools": {
"update_status": {
"limits": [
{
"counter": "update_status_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}update_status 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.
Free to start. No card required.
Update status for multiple sources in a single transaction. It is categorised as a Write tool in the literateMCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the literate MCP server in PolicyLayer and add a rule for update_status: 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 literateMCP. Nothing to install.
update_status 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 update_status 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 update_status. 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.
update_status is provided by the literate MCP server (zongmin-yu/sqlite-literature-management-fastmcp-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from literateMCP, 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.
15 literateMCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.