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ClockNext MCP Server

ClockNext MCP Server

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ClockNext: bulk import customers

clocknext_bulk_import_customers

Bulk-create up to 200 ClockNext customers in a single request for backfilling a user base. Per-row results prevent one bad record from aborting the batch.

Instructions

Bulk-create ClockNext customers in ONE request — for backfilling an existing user base. Pass an array of customers (each needs name + email; up to 200 per call). The whole batch goes to the server in a single call and comes back with a PER-ROW result — created id, or an error — so one duplicate/bad row never aborts the batch. Match results back to your users by email. Runs against a private, MCP-only bulk endpoint (no SDK / public API); for a larger base, call it again in ≤200-row chunks.

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": {
      "customers": "<customers>"
    },
    "name": "clocknext_bulk_import_customers"
  }
}

Input Schema

NameRequiredDescriptionDefault
customersYesThe customers to create (name + email required each; ≤200 per call).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.0

TDQS

A4.2/5.0
Behavior4/5

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

Beyond the annotations (readOnlyHint=false, idempotentHint=false), the description adds valuable behavioral detail: the batch returns a per-row result with either a created id or an error, and one bad row never aborts the batch. It also discloses that this is a private MCP-only endpoint. This is significant context not inferable from the annotations or schema.

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?

The description is concise and front-loaded, with the core purpose in the first clause. It packs essential information (batch behavior, per-row results, size limit, chunking) into a few dense sentences without wordiness or repetition. Every sentence contributes unique value.

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

Completeness4/5

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

For a bulk import tool with a single array parameter and no output schema, the description covers the key operational aspects: required fields, max batch size, per-row results, error handling, and how to scale. It does not provide an exact response schema, but the description's logical model of per-row results is sufficient for an agent to understand what to expect.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline is 3. The description adds that each customer needs name + email and the 200-per-call limit, but both are already in the schema (required fields and maxItems). The 'match back by email' note adds context but is also hinted in the email field description. No negative impact, but minimal extra value.

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?

The description opens with 'Bulk-create ClockNext customers in ONE request', which states the exact action (bulk create), resource (ClockNext customers), and scope (multiple in one request). It also mentions 'backfilling an existing user base', clearly positioning it relative to single-customer creation tools like create_customer.

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?

The description provides clear usage context: it is for backfilling an existing user base and uses a private bulk endpoint. It also gives chunking advice for larger bases. However, it does not explicitly contrast with the single-create sibling (create_customer) or mention scenarios where bulk import is inappropriate, so it stops short of full exclusions.

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

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