MF Invoice MCP

mf_create_billing_from_quote

Convert quotes to invoices by specifying billing details and payment terms. This tool automates invoice creation from existing quotes within the MoneyForward Cloud Invoice system.

Instructions

見積書から請求書を作成します

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": {
      "quote_id": "<quote_id>"
    },
    "name": "mf_create_billing_from_quote"
  }
}

Input Schema

Name	Required	Description
`quote_id`	Yes	元となる見積書のID
`billing_date`	No	請求日（YYYY-MM-DD）
`due_date`	No	支払期限（YYYY-MM-DD）
`sales_date`	No	売上日（YYYY-MM-DD）
`title`	No	請求書タイトル
`memo`	No	メモ
`payment_condition`	No	支払条件

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.1Feb 1, 2026

TDQS

C2.9/5.0

Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool creates an invoice from a quote but doesn't mention whether this is a mutating operation, what permissions are required, whether the quote is modified, what happens on failure, or what the response contains. For a creation tool with zero annotation coverage, this is insufficient.

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 a single, efficient Japanese sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded with the core functionality.

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

Completeness2/5

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

For a creation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns, what side effects occur, or how it differs from similar sibling tools. The 100% schema coverage helps with parameters, but overall context for proper tool selection and invocation is lacking.

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%, providing clear documentation for all 7 parameters. The description doesn't add any additional parameter semantics beyond what's in the schema, but the schema adequately covers parameter purposes and formats. The baseline score of 3 reflects that the schema does the heavy lifting.

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 the action ('作成します' - creates) and resource ('請求書' - invoice) from a source ('見積書から' - from quote). It's specific about the transformation process but doesn't explicitly differentiate from sibling tools like 'mf_convert_quote_to_billing' which appears to serve a similar purpose.

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

Usage Guidelines2/5

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

No guidance is provided about when to use this tool versus alternatives like 'mf_convert_quote_to_billing' or 'mf_create_billing'. The description only states what the tool does without indicating appropriate contexts, prerequisites, or exclusions.

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