@kimagure-dd/xirr-mcp
@kimagure-dd/xirr-mcp
Servidor MCP para el cálculo de la XIRR (Tasa Interna de Retorno Extendida), con soporte integrado para el CSV de transacciones de Rakuten Securities (楽天証券).
Conéctalo a Claude Desktop o Claude Code, facilítale un CSV exportado de tu bróker y pregunta:
「この CSV と現在の評価額 ¥1,500,000 で、実績年利を計算して」
Claude calculará la XIRR por ti —teniendo en cuenta las aportaciones y retiradas irregulares— y explicará el resultado.
Características
🧮
calculate_xirr— XIRR a partir de series de flujo de caja arbitrarias + valoración actual📄
parse_rakuten_csv— Analiza el CSV de transacciones de Rakuten Securities (取引履歴) y lo convierte en flujos de caja normalizados🔌 Servidor MCP puro stdio, no requiere acceso a la red
📦 Configuración en tiempo de ejecución cero, comando
npxúnico
Related MCP server: ibkr-mcp
Instalación y configuración
Claude Desktop
Edita ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) o %APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"xirr": {
"command": "npx",
"args": ["-y", "@kimagure-dd/xirr-mcp"]
}
}
}Reinicia Claude Desktop. Deberían aparecer las herramientas calculate_xirr y parse_rakuten_csv.
Claude Code
claude mcp add xirr -- npx -y @kimagure-dd/xirr-mcpEjemplos de uso
Cálculo directo
Pregunta a Claude:
「以下のキャッシュフローで XIRR を計算して。2020-01-01 に 100万円投資、2022-01-01 に 50万円追加、現在(2025-01-01)の評価額 200万円」
Claude llamará a calculate_xirr con la entrada estructurada y devolverá:
{
"annualRate": 12.34,
"annualRateFormatted": "12.34%",
"totalInvestment": 1500000,
"totalGain": 500000,
"gainRateFormatted": "33.33%",
"converged": true
}Desde el CSV de Rakuten Securities
Inicia sesión en Rakuten Securities → Historial de transacciones (取引履歴) → Descargar CSV
(Como se descarga en Shift_JIS, conviértelo a UTF-8)
Pasa el contenido del archivo a Claude y solicita: "Calcula la rentabilidad anual real con esto. La valoración actual es ¥X"
Claude enviará automáticamente el CSV a través de parse_rakuten_csv → calculate_xirr.
Referencia de herramientas
calculate_xirr
Calcula la XIRR a partir de una lista de flujos de caja fechados y una valoración actual.
Entrada:
Campo | Tipo | Descripción |
| array | Lista de |
| number | Valoración actual de la cartera. |
| string | YYYY-MM-DD. Fecha de |
Salida:
Campo | Tipo | Descripción |
| number | Rentabilidad anualizada como porcentaje. |
| number | Tasa mensual (compuesta a anual). |
| number | Suma de todos los flujos de caja. |
| number |
|
| number | Ganancia total como porcentaje de la inversión. |
| boolean | Verdadero si el solucionador iterativo convergió. |
parse_rakuten_csv
Analiza un CSV de transacciones de Rakuten Securities.
Entrada:
Campo | Tipo | Descripción |
| string | Texto CSV sin procesar (decodificado en UTF-8). |
Cabeceras CSV requeridas:
約定日, 取引, ファンド名, 受渡金額/(ポイント利用)[円]
Comportamiento:
Filas
買付→ cantidad positiva (inversión)Otros tipos de transacciones (ej.
売却) → cantidad negativa (retirada)Las filas no válidas se omiten con advertencias
Método de cálculo
Iteración de Newton-Raphson como solucionador principal
Alternativa de bisección cuando Newton no logra converger
Unidad de tiempo: meses (usando 365.25 / 12 días por mes)
Umbral de convergencia: 1e-7
Se utiliza la misma lógica en la calculadora XIRR basada en navegador en kimagure-dd.dev, por lo que los resultados son idénticos.
Descargo de responsabilidad
Esta herramienta calcula el rendimiento de la inversión solo con fines informativos. No se consideran impuestos, comisiones de transacción ni conversión de divisas. El resultado no constituye asesoramiento de inversión.
Desarrollo
npm install
npm run build
npm testPara probar el servidor localmente antes de publicar:
npm pack
# Then point Claude Desktop to the .tgz pathLicencia
MIT © kimagure-dd
Relacionado
🌐 kimagure-dd.dev — Calculadoras financieras basadas en navegador
Available Tools
2 toolscalculate_xirrA
Calculate XIRR (Extended Internal Rate of Return) from a series of dated cash flows and a current portfolio valuation. Returns annualized rate, monthly rate, total gain, and convergence status. Useful for measuring actual investment performance accounting for irregular contributions and withdrawals.
| Name | Required | Description | Default |
|---|---|---|---|
| cashFlows | Yes | List of cash flows. Use positive amounts for investments (buy), negative for withdrawals (sell). | |
| currentValue | Yes | Current valuation of the portfolio at valuationDate. | |
| valuationDate | Yes | Date of the current valuation in YYYY-MM-DD format. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It indicates the outputs (annualized rate, monthly rate, total gain, convergence status) but does not mention potential issues like convergence failures, input validation, or performance limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loaded with the purpose and return values. Every word is informative and there is no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema, the description adequately lists the return values (annualized rate, monthly rate, total gain, convergence status). It covers the essential outputs for a financial calculation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage, so the description adds limited semantic value beyond what's already documented. It reiterates that positive amounts are investments, which is already in the schema, but does not provide new details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Calculate XIRR' and the resource 'from a series of dated cash flows and a current portfolio valuation'. It distinguishes this tool from its sibling parse_rakuten_csv, which handles CSV parsing, by focusing on financial computation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use the tool ('useful for measuring actual investment performance...'), but does not explicitly mention when not to use it or provide alternatives. However, given the distinct sibling tool, no confusion arises.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
parse_rakuten_csvA
Parse a Rakuten Securities transaction CSV (取引履歴) and convert it into a normalized cash flow list. Handles 買付/売却 transaction types automatically. The output can be fed directly into calculate_xirr.
| Name | Required | Description | Default |
|---|---|---|---|
| csvContent | Yes | Raw CSV text exported from Rakuten Securities. Note: Rakuten exports are typically Shift_JIS encoded; decode to UTF-8 before passing. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the automatic handling of transaction types and encoding issues, but lacks details on error behavior, file size limits, or other edge cases. It is partially transparent but leaves gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences that are efficiently front-loaded. The first sentence states the core purpose, the second adds key details. Every sentence is meaningful with no superfluous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool (1 param, no output schema), the description covers input format, handling, and integration with calculate_xirr. It could mention the output structure more explicitly, but it is sufficient for an agent to understand usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% coverage with a single parameter. The description adds value by explaining the parameter is raw CSV text and specifically notes the Shift_JIS encoding issue, which is critical for correct usage. This exceeds the baseline of 3 for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool parses Rakuten Securities transaction CSV and converts to normalized cash flow list, handling specific transaction types. It implicitly distinguishes from the sibling tool calculate_xirr by indicating the output feeds into it.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says when to use the tool (when you have a Rakuten Securities CSV) and hints at the workflow with calculate_xirr. It provides encoding context but doesn't explicitly state when not to use it or list alternatives, though the sibling count is low.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
2 tool updates
v0.1.0- First observed
calculate_xirr - First observed
parse_rakuten_csv
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: parse_rakuten_csv converts a specific CSV into cash flows, and calculate_xirr performs the actual rate calculation. No overlap exists.
Both tools follow a consistent verb_noun pattern using snake_case: parse_rakuten_csv and calculate_xirr. Perfectly consistent.
With only 2 tools, the server is very focused but appropriately scoped for the specific use case of Rakuten CSV processing and XIRR calculation. A slightly broader tool count could be argued, but it's reasonable.
For the domain of computing XIRR from Rakuten CSV data, the server is complete. The parse-then-calculate workflow covers all necessary steps without missing functionality.
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