update_service
Update an existing booking service. Pass only the fields you want to change.
This record as markdown: /tools/io-favcrm-favcrm/update-service.md
What update_service does on FavCRM
AI agents use update_service 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 | string | — | Decimal string, e.g. "80.00" |
status | string | — | Status filter |
capacity | number | — | Participants per slot |
serviceId | string | Yes | Service ID to update |
categoryId | object | — | Category ID |
visibility | string | — | Visibility: public | members_only | hidden |
description | string | — | Description |
requireLogin | boolean | — | If true, guests cannot book without an account |
requiresStaff | boolean | — | Whether the service requires staff assignment |
commissionType | object | — | Commission type: "fixed" or "percentage" |
commissionValue | object | — | Commission amount as decimal string |
Parameters from the server's own tool schema.
Why update_service is rated Medium
This tool creates or modifies data reversibly within the CRM system. It updates service records (likely bookings or service configurations) without deleting or irreversibly destroying information. The context of a service business CRM suggests this operates on scheduling, service details, or booking metadata.
From the tool's definition Tool name 'update_service' and description 'Update an existing booking service. Pass only the fields you want to change.' indicate modification of existing data in a reversible manner.
Risk signalsHigh parameter count (17 properties)
Attacks that exploit this kind of access
The rule that runs update_service 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, this is the rule to start with:
update_service 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 call is checked against it from then on.
Questions about update_service
Update an existing booking service. 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 accepts 12 parameters: name, price, status, capacity, serviceId, categoryId, visibility, description, requireLogin, requiresStaff, commissionType, commissionValue. Required: serviceId. 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: 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 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 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. 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 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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