MF Invoice MCP

mf_update_quote

Update quotes in MoneyForward Cloud Invoice by modifying details like title, dates, items, and tax information to maintain accurate billing records.

Instructions

見積書を更新します

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_update_quote"
  }
}

Input Schema

Name	Required	Description
`quote_id`	Yes	見積書ID
`title`	No	見積書タイトル
`memo`	No	メモ
`quote_date`	No	見積日（YYYY-MM-DD）
`expired_date`	No	有効期限（YYYY-MM-DD）
`items`	No	明細行（指定時は全置換）

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.1Feb 1, 2026

TDQS

C2.7/5.0

Behavior2/5

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

With no annotations provided, the description carries full burden but only states the action ('updates a quote') without disclosing behavioral traits. It doesn't mention whether this is a destructive operation, what permissions are required, how errors are handled, or what the response looks like (since no output schema exists). This is inadequate for a mutation tool with zero annotation coverage.

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 a single sentence ('見積書を更新します'), which is front-loaded and wastes no words. For a tool with a well-documented schema, this brevity is appropriate, though it may sacrifice completeness.

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?

Given the complexity (6 parameters, nested items array, mutation operation) and lack of annotations and output schema, the description is incomplete. It doesn't explain the tool's behavior, return values, or usage context, leaving significant gaps for an AI agent to understand how to invoke it correctly beyond the basic schema.

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?

The schema description coverage is 100%, with detailed descriptions for all parameters (e.g., quote_id, items with full replacement). The description adds no additional parameter semantics beyond what's in the schema, so it meets the baseline of 3 where the schema does the heavy lifting, but doesn't compensate or enhance understanding.

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

Purpose3/5

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

The description '見積書を更新します' (Updates a quote) clearly states the verb (update) and resource (quote), but it's quite generic and doesn't differentiate from sibling tools like mf_update_billing or specify what aspects of a quote can be updated. It avoids being a tautology with the name (mf_update_quote), but lacks specificity about scope.

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 on when to use this tool versus alternatives like mf_create_quote or mf_get_quote, nor are there any prerequisites mentioned (e.g., needing an existing quote_id). The description implies usage for updates but offers no context about constraints or typical scenarios.

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