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Alegra MCP Server and API by Cotlet

Record payment in Alegra

alegra_record_payment
Read-onlyIdempotent

Record payment in the user's own Alegra account from ChatGPT, Claude or any AI agent. Returns how to do it in Alegra step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's Alegra Cloud Browser. Alegra's official API: Yes, Alegra has a REST API for invoices, contacts, payments and items (checked 14 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": "alegra_record_payment"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior4/5

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

Annotations declare readOnlyHint=true and destructiveHint=false, and the description reinforces this by stating the tool "opens nothing by itself" and merely returns procedural output. It adds useful context about the return shape (steps with screens/buttons/fields) but says nothing about account scoping or whether the instructions are account-specific.

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

Conciseness3/5

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

The critical clarification about what the tool actually does is placed second, after a marketing-style opener naming ChatGPT/Claude. The final sentence about Alegra's official REST API is irrelevant noise, since this tool returns UI instructions rather than calling the API.

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 input schema and no output schema, the description carries the burden of explaining the return value, and it does so adequately by describing step-by-step screens, buttons and fields. The trailing API sentence adds confusion rather than missing coverage.

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 there is nothing for the description to disambiguate; the baseline for a no-parameter schema applies. The description correctly implies the tool needs no input because it only returns instructions.

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 states a specific behavior: it returns step-by-step instructions for recording a payment in Alegra (screens, buttons, fields) rather than performing the action. That said, the opening sentence ("Record payment in the user's own Alegra account from ChatGPT, Claude or any AI agent") reads like a write operation and must be corrected by the following sentence, and no sibling (e.g. cotlet_app_guide) is named for differentiation.

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?

It gives a clear usage chain: call this to get the procedure, then execute it with the cotlet_browser_* tools in the user's Alegra Cloud Browser, and it explicitly states the tool opens nothing by itself. It stops short of naming alternatives or exclusions beyond that workflow.

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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