update_scheduled_maintenance_state_timeline
Update an existing Scheduled Maintenance State Timeline in OneUptime. Only include the fields you want to change - unspecified fields will remain unchanged. Use get_scheduled_maintenance_state_timeline afterwards to see the updated record.
This record as markdown: /tools/com-oneuptime-mcp/update-scheduled-maintenance-state-timeline.md
What update_scheduled_maintenance_state_timeline does on OneUptime
AI agents use update_scheduled_maintenance_state_timeline to create or update resources in OneUptime, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your OneUptime environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
id | string | Yes | The unique identifier (UUID) of the Scheduled Maintenance State Timeline to update. Required. Use list_scheduled_maintenance_state_timelines to find IDs. |
startsAt | object | — | When did this status change? Correct this when the recorded time is wrong - every measurement derived from this timeline is recomputed from the corrected value. |
scheduledMaintenanceStateId | string | — | Scheduled Maintenance State ID. Which state does this event belongs to? |
Parameters from the server's own tool schema.
Why update_scheduled_maintenance_state_timeline is rated Medium
An AI agent can call update_scheduled_maintenance_state_timeline faster than any human can review: one bad instruction and it creates or modifies resources in OneUptime by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
The rule that runs update_scheduled_maintenance_state_timeline safely
PolicyLayer is an MCP gateway: it sits between your AI agents and OneUptime, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For update_scheduled_maintenance_state_timeline, this is the rule to start with:
update_scheduled_maintenance_state_timeline 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.
The button opens the PolicyLayer dashboard: create your workspace, connect OneUptime, apply this rule, and every update_scheduled_maintenance_state_timeline call is checked against it from then on.
Questions about update_scheduled_maintenance_state_timeline
Update an existing Scheduled Maintenance State Timeline in OneUptime. Only include the fields you want to change - unspecified fields will remain unchanged. Use get_scheduled_maintenance_state_timeline afterwards to see the updated record. It is categorised as a Write tool in the OneUptime MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
update_scheduled_maintenance_state_timeline accepts 3 parameters: id, startsAt, scheduledMaintenanceStateId. Required: id. The full parameter table on this page comes from the server's own tool schema.
Register the OneUptime MCP server in PolicyLayer and add a rule for update_scheduled_maintenance_state_timeline: 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 OneUptime. Nothing to install.
update_scheduled_maintenance_state_timeline 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_scheduled_maintenance_state_timeline 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_scheduled_maintenance_state_timeline. 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_scheduled_maintenance_state_timeline is provided by the OneUptime MCP server (https://oneuptime.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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