AI agents use update_story_schedule to create or update resources in Storyblok MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Storyblok MCP Server environment.
This tool modifies schedule metadata for stories, which is a reversible change to content configuration. It does not execute arbitrary code (Execute), permanently delete data (Destructive), or move money (Financial).
From the tool's definition Tool name 'update_story_schedule' indicates modification of scheduling settings for stories in Storyblok. The sibling tools context shows this server manages Storyblok content assets including stories, with tools like 'bulk_publish_stories' and…
Documented attack patterns abuse exactly the kind of access update_story_schedule gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Storyblok MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for update_story_schedule:
{
"version": "1",
"default": "deny",
"tools": {
"update_story_schedule": {
"limits": [
{
"counter": "update_story_schedule_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
} update_story_schedule 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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update_story_schedule. It is categorised as a Write tool in the Storyblok MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Storyblok MCP Server MCP server in PolicyLayer and add a rule for update_story_schedule: 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 Storyblok MCP Server. Nothing to install.
update_story_schedule 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_story_schedule 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_story_schedule. 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_story_schedule is provided by the Storyblok MCP Server MCP server (kiran1689/storyblok-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Storyblok 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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159 Storyblok MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.