update_service_package
Update an existing service package. Pass only the fields you want to change.
This record as markdown: /tools/io-favcrm-favcrm/update-service-package.md
What update_service_package does on FavCRM
AI agents use update_service_package to create or update resources in FavCRM, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your FavCRM environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
name | string | — | Name |
price | number | — | Decimal string, e.g. "80.00" |
status | string | — | Status filter |
packageId | string | Yes | Service package ID to update |
validDays | integer | — | Validity period in days |
description | object | — | Description |
sessionCount | integer | — | Number of sessions in the package |
applicableType | string | — | What this package applies to: services | products | both |
applicableItems | array | — | Item IDs the package can be redeemed against |
Parameters from the server's own tool schema.
Why update_service_package is rated Medium
This tool creates or modifies data (service package configuration) in a reversible manner. It does not delete data (would be Destructive), execute code (would be Execute), or move money (would be Financial). The blast radius is medium because misconfigured service packages could affect business operations, pricing, or customer bookings, but changes can typically be reversed by updating again.
From the tool's definition Tool name 'update_service_package' and description 'Update an existing service package. Pass only the fields you want to change.' indicates modification of existing data.
Risk signalsHigh parameter count (11 properties)
Attacks that exploit this kind of access
The rule that runs update_service_package safely
PolicyLayer is an MCP gateway: it sits between your AI agents and FavCRM, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For update_service_package, this is the rule to start with:
update_service_package 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 FavCRM, apply this rule, and every update_service_package call is checked against it from then on.
Questions about update_service_package
Update an existing service package. Pass only the fields you want to change. It is categorised as a Write tool in the FavCRM MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
update_service_package accepts 9 parameters: name, price, status, packageId, validDays, description, sessionCount, applicableType, applicableItems. Required: packageId. The full parameter table on this page comes from the server's own tool schema.
Register the FavCRM MCP server in PolicyLayer and add a rule for update_service_package: 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 FavCRM. Nothing to install.
update_service_package 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_service_package 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_service_package. 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_service_package is provided by the FavCRM MCP server (https://api.favcrm.io/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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