clover-mcp

update_customer

DestructiveIdempotent

Update a customer's name or marketing opt-in. Only specified fields change, with dry-run preview and confirmation before writing.

Instructions

Modifies merchant data. Update a customer's name and/or marketing opt-in.

Only the fields you pass change. Previews on dry_run; confirms via MCP elicitation or confirm=True before writing. Requires CUSTOMERS_W.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "customer_id": "<customer_id>"
    },
    "name": "update_customer"
  }
}

Input Schema

Name	Required	Description	Default
`confirm`	No
`dry_run`	No
`last_name`	No
`first_name`	No
`customer_id`	Yes
`marketing_allowed`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.7.0Aug 7, 2026

TDQS

A4.7/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond annotations (readOnly=false, destructive=true), the description discloses partial-field updates ('Only the fields you pass change'), the dry-run preview behavior, the confirmation mechanism (MCP elicitation or confirm=True), and the required permission. These are not visible in the schema or annotations, providing excellent behavioral transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences: the first states purpose, the second explains partial-update behavior, the third covers dry_run, confirmation, and permissions. Every sentence adds value; no filler or redundant details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers purpose, permissions, update granularity, and safety (confirmation). With an output schema present and annotations providing safety hints, the description is complete for an agent to decide when and how to use it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description carries the burden. It maps fields to 'name' (first_name, last_name) and 'marketing opt-in' (marketing_allowed), and explains the semantics of dry_run and confirm. However, it doesn't clarify the difference between omitted vs null parameters (e.g., whether null clears a field), leaving some ambiguity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Starts with 'Update a customer's name and/or marketing opt-in' which names the verb (update), resource (customer), and specific fields. This clearly distinguishes it from create_customer (new records) and get_customer (read-only).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

While it doesn't explicitly name alternatives, it provides clear context: this tool updates an existing customer's name and marketing opt-in, implying it is for modifications after creation. It also mentions the permission requirement (CUSTOMERS_W) and the dry_run/confirmation flow, adding practical usage guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server