Ordrestyring MCP Server and API by Cotlet

Create invoice draft in Ordrestyring

ordrestyring_create_invoice_draft

Read-onlyIdempotent

Create invoice draft in the user's own Ordrestyring account from ChatGPT, Claude or any AI agent. Returns how to do it in Ordrestyring step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's Ordrestyring Cloud Browser. Ordrestyring's official API: Ordrestyring has a GraphQL API and no official MCP server (checked 31 Oct 2026).

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": "ordrestyring_create_invoice_draft"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 9, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations declare readOnlyHint=true and destructiveHint=false; the description adds the non-obvious behavior that it 'opens nothing by itself' and merely returns a procedure, which is exactly the fact an agent would otherwise misinterpret given the 'create' name. It does not cover authentication or what happens if the Cloud Browser session is unavailable, but the core behavioral surprise is disclosed.

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

Conciseness4/5

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

Front-loaded with the action, then the return shape, then the handoff to browser tools. The phrase 'from ChatGPT, Claude or any AI agent' is filler that could be cut, and the closing API note is tangential, though it does explain why a guide-based tool exists.

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?

With no parameters and no output schema, the description carries the burden of describing what is returned, and it does (step-by-step screens, buttons, fields). The only gap is the absence of any note on preconditions, such as the user needing an Ordrestyring Cloud Browser session before the follow-up tools can run.

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?

The tool takes zero parameters, so the baseline is 4; there is nothing the description could add or omit on argument meaning. The schema coverage is 100% and the description correctly refrains from inventing argument behavior.

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?

States a specific verb and resource (create an invoice draft in Ordrestyring) and, critically, clarifies that the tool itself only returns instructions rather than performing the action. This resolves the misleading-looking name and tells the agent exactly what artifact it gets back: step-by-step screens, buttons and fields.

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?

Gives clear usage context: call this first, then execute the steps with the cotlet_browser_* tools in the user's Ordrestyring Cloud Browser, which names the concrete alternative path. It stops short of explicit when-not conditions (e.g. what to do if the user only wants to read invoices), so it is clear but not fully bounded.

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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