adaptercloud_scheduler_jobs_update

Update a scheduled job (cron expression, executor config, retry policy, etc.). At least one field must be provided. Returns the updated ScheduledJob.

SERVERAdaptercloud SOURCE@burdenoff/adaptercloud-mcp

Medium RISK CLASS

Category Write

Parameters 101 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/burdenoff-adaptercloud-mcp/adaptercloud-scheduler-jobs-update.md

WHAT IT DOES

What adaptercloud_scheduler_jobs_update does on Adaptercloud

AI agents use adaptercloud_scheduler_jobs_update to create or update resources in Adaptercloud, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Adaptercloud environment.

Parameter	Type	Required	Description
`id`	string	Yes	Job ID
`name`	string	—	Updated job name
`endDate`	string	—	Updated end date (ISO-8601)
`interval`	integer	—	Updated interval (INTERVAL jobs only)
`maxRetries`	integer	—	Max retry attempts on failure
`description`	string	—	Updated description
`changeReason`	string	—	Audit-trail reason for the change
`intervalUnit`	string	—	Interval unit (SECONDS\|MINUTES\|HOURS\|DAYS, will be uppercased)
`cronExpression`	string	—	Updated cron expression (CRON jobs only)
`executorConfig`	object	—	Updated executor configuration

Parameters from the server's own tool schema.

RISK

Why adaptercloud_scheduler_jobs_update is rated Medium

An AI agent can call adaptercloud_scheduler_jobs_update faster than any human can review: one bad instruction and it creates or modifies resources in Adaptercloud by the hundred, each call as confident as the last.

Risk signalsHigh parameter count (10 properties)

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs adaptercloud_scheduler_jobs_update safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Adaptercloud, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For adaptercloud_scheduler_jobs_update, this is the rule to start with:

adaptercloud_scheduler_jobs_update Rate-limited

adaptercloud_scheduler_jobs_update 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "adaptercloud_scheduler_jobs_update": {
      "limits": [
        {
          "counter": "adaptercloud_scheduler_jobs_update_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Adaptercloud, apply this rule, and every adaptercloud_scheduler_jobs_update call is checked against it from then on.

FAQ

Questions about adaptercloud_scheduler_jobs_update

What does the adaptercloud_scheduler_jobs_update tool do? +

Update a scheduled job (cron expression, executor config, retry policy, etc.). At least one field must be provided. Returns the updated ScheduledJob. It is categorised as a Write tool in the Adaptercloud MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

What parameters does adaptercloud_scheduler_jobs_update accept? +

adaptercloud_scheduler_jobs_update accepts 10 parameters: id, name, endDate, interval, maxRetries, description, changeReason, intervalUnit, cronExpression, executorConfig. Required: id. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on adaptercloud_scheduler_jobs_update? +

Register the Adaptercloud MCP server in PolicyLayer and add a rule for adaptercloud_scheduler_jobs_update: 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 Adaptercloud. Nothing to install.

What risk level is adaptercloud_scheduler_jobs_update? +

adaptercloud_scheduler_jobs_update is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit adaptercloud_scheduler_jobs_update? +

Yes. Add a rate_limit block to the adaptercloud_scheduler_jobs_update 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.

How do I block adaptercloud_scheduler_jobs_update completely? +

Set action: deny in the PolicyLayer policy for adaptercloud_scheduler_jobs_update. 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.

What MCP server provides adaptercloud_scheduler_jobs_update? +

adaptercloud_scheduler_jobs_update is provided by the Adaptercloud MCP server (@burdenoff/adaptercloud-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

KEEP EXPLORING

More on Adaptercloud, and thousands of servers like it.

This server

All 396 Adaptercloud tools →

Across the catalogue

aroflo_create_or_update_record on AroFlo MCP → The MCP Attack Database →

Guides

Govern customer-ops agents →Argument validation →Scoped token →