MCP Cliniko Server

demo_invoice_generation

Generate test patients and appointments to demonstrate invoice creation workflows in Cliniko, using sample data for training and system testing.

Instructions

Demo: Generate test patients and appointments, then show how to create invoices. NOTE: Cliniko API is READ-ONLY for invoices - they must be created via the web interface.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "demo_invoice_generation"
  }
}

Input Schema

Name	Required	Description	Default
`target_date`	No	Target date for appointments (YYYY-MM-DD format). Defaults to today
`num_patients`	No	Number of test patients to generate (max 10 for rate limits)
`num_appointments`	No	Number of appointments to generate (max 20 for rate limits)
`clear_existing`	No	Clear existing test data before generating new data
`display_format`	No	How to display the results	detailed

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Apr 15, 2026

TDQS

A3.6/5.0

Behavior3/5

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

No annotations provided, so description must disclose all behaviors. It mentions generating test data and the invoice limitation, but fails to state that clear_existing defaults to true, which could delete existing data. The demo nature is implicit, but side effects are not fully transparent.

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 extremely concise with two short sentences, no filler, and front-loads the purpose. Every part is necessary and immediately informative.

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 demo tool with no output schema and no annotations, the description covers the core purpose and key limitation. It lacks detail on return value format or expected output, but the demo context makes this acceptable. It is sufficiently complete for its intended use.

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 coverage is 100%, so baseline is 3. The description adds no parameter-specific meaning beyond the schema. It repeats the general demo context but does not elaborate on how parameters affect the outcome.

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

Purpose4/5

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

The description clearly states it generates test patients/appointments and demonstrates invoice creation, noting the API's read-only limitation. This distinguishes it as a demo tool, but its purpose overlaps with sibling generate_test_data tools, lacking explicit differentiation.

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

Usage Guidelines3/5

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

The description indicates it's a demo for invoice generation, but provides no guidance on when to use this tool vs. alternatives like generate_test_data or how_to_create_invoices. Context from sibling tools suggests overlap, but no exclusions or recommendations are given.

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