Lunch Money MCP Server
Servidor MCP de Lunch Money
Un servidor del Protocolo de Contexto de Modelo (MCP) que permite a los agentes de IA interactuar con tus datos de finanzas personales de Lunch Money.
Características
Este servidor MCP expone 15 herramientas para gestionar tus datos financieros:
Usuario y Cuenta
get_user— Obtén tu perfil e información de cuenta
Categorías
get_categories— Lista todas las categorías (planas o anidadas)create_category— Crea nuevas categorías personalizadasupdate_category— Modifica categorías existentes
Transacciones
get_transactions— Consulta transacciones con filtros (rango de fechas, categoría, estado, etc.)create_transaction— Añade nuevas transacciones (individuales o por lotes de hasta 500)update_transaction— Actualiza transacciones o divídelas en múltiples entradas
Activos y Cuentas
get_assets— Lista los activos gestionados manualmentecreate_asset— Añade nuevos activos manualesget_plaid_accounts— Lista las cuentas bancarias conectadas mediante Plaidtrigger_plaid_fetch— Activa la sincronización de cuentas de Plaid
Presupuestos y Planificación
get_budgets— Visualiza presupuestos y gastos para cualquier rango de fechasupsert_budget— Establece o actualiza importes presupuestariosget_recurring_items— Visualiza gastos e ingresos recurrentes
Etiquetas
get_tags— Lista todas las etiquetas de transacciones
Related MCP server: YNAB Assistant
Requisitos previos
Node.js 18 o superior
Una cuenta de Lunch Money con acceso a la API
Una clave de API de Lunch Money desde la página de desarrolladores
Instalación
Opción 1: Clonar y compilar (transporte stdio local)
Para uso local con Cursor, Claude Desktop u otros clientes MCP basados en stdio:
# Clone the repository
git clone https://github.com/yourusername/lunchmoney-mcp.git
cd lunchmoney-mcp
# Install dependencies
npm install
# Build the TypeScript
npm run buildOpción 2: Cloudflare Workers (transporte HTTP remoto)
Despliega como un servidor MCP remoto accesible vía HTTP:
# Clone the repository
git clone https://github.com/yourusername/lunchmoney-mcp.git
cd lunchmoney-mcp
# Install dependencies
npm install
# Set your API key as a secret
npx wrangler secret put LUNCH_MONEY_API_KEY
# Enter your Lunch Money API key when prompted
# Deploy to Cloudflare Workers
npm run deployOpción 3: Usar con npx (solo local)
Puedes ejecutar el servidor MCP directamente sin clonar:
npx -y lunchmoney-mcpNota: Aún necesitarás configurar la variable de entorno LUNCH_MONEY_API_KEY.
Configuración
Obtener tu clave de API
Inicia sesión en Lunch Money
Genera una nueva clave de API
Copia la clave (¡mantenla segura!)
Cursor IDE
Añade a tu configuración MCP de Cursor (~/.cursor/mcp.json):
{
"mcpServers": {
"lunchmoney": {
"command": "node",
"args": ["/path/to/lunchmoney-mcp/dist/index.js"],
"env": {
"LUNCH_MONEY_API_KEY": "your_api_key_here"
}
}
}
}O con npx:
{
"mcpServers": {
"lunchmoney": {
"command": "npx",
"args": ["-y", "lunchmoney-mcp"],
"env": {
"LUNCH_MONEY_API_KEY": "your_api_key_here"
}
}
}
}Claude Desktop
Añade a tu configuración de Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json en macOS):
{
"mcpServers": {
"lunchmoney": {
"command": "node",
"args": ["/path/to/lunchmoney-mcp/dist/index.js"],
"env": {
"LUNCH_MONEY_API_KEY": "your_api_key_here"
}
}
}
}Otros clientes MCP
Cualquier cliente MCP que soporte transporte stdio puede usar este servidor. Configura la variable de entorno LUNCH_MONEY_API_KEY y ejecuta:
node /path/to/lunchmoney-mcp/dist/index.jsMCP remoto vía Cloudflare Workers (Trae tu propia clave API)
El despliegue en Cloudflare Workers está diseñado como un servidor MCP público donde cada usuario aporta su propia clave API. El servidor nunca almacena ninguna clave API.
Cómo funciona:
Despliega el servidor en Cloudflare Workers (o usa una instancia compartida)
Cada usuario se conecta con su propia clave API de Lunch Money
La clave API se envía con cada solicitud en el encabezado
X-LunchMoney-API-Key
Conectando con el proxy mcp-remote:
{
"mcpServers": {
"lunchmoney": {
"command": "npx",
"args": ["mcp-remote", "https://lunchmoney-mcp.your-subdomain.workers.dev/mcp"],
"env": {
"MCP_HEADERS": "X-LunchMoney-API-Key: your_api_key_here"
}
}
}
}Nota: El proxy mcp-remote debe soportar encabezados personalizados. Es posible que algunos clientes MCP aún no soporten esto.
⚠️ Trata tu archivo
mcp.jsoncomo un archivo de credenciales. Ahora contiene tu clave API de Lunch Money. Nunca lo subas a un repositorio Git (incluyendo repositorios de archivos de configuración). Añádelo a.gitignoresi reside dentro de uno. Cualquiera con acceso de lectura a este archivo puede leer y modificar tus datos de Lunch Money.
Seguridad: Este es el modelo más seguro porque:
El servidor nunca almacena ninguna clave API
Cada usuario solo accede a sus propios datos
Las claves API se pasan por solicitud, no se almacenan en el servidor
El worker público aplica límites de tasa por IP y nunca registra cuerpos o encabezados de solicitud
Despliegue en Cloudflare Workers (Servidor Público)
Esto crea un servidor MCP público que cualquiera puede usar con su propia clave API. El servidor no almacena ninguna credencial.
Requisitos previos
Una cuenta de Cloudflare (el nivel gratuito funciona)
Wrangler CLI instalado
Despliegue
Instalar dependencias:
npm installDesplegar en Cloudflare Workers:
npm run deploy¡Tu servidor MCP público ya está activo! La URL se mostrará en la salida:
https://lunchmoney-mcp.your-account.workers.dev/mcpOpcional: Puedes establecer una clave API predeterminada para pruebas:
npx wrangler secret put LUNCH_MONEY_API_KEYCómo se conectan los usuarios
Los usuarios se conectan a tu servidor público con su propia clave API de Lunch Money:
{
"mcpServers": {
"lunchmoney": {
"command": "npx",
"args": ["mcp-remote", "https://lunchmoney-mcp.your-account.workers.dev/mcp"],
"env": {
"MCP_HEADERS": "X-LunchMoney-API-Key: their_api_key_here"
}
}
}
}Desarrollo local con Wrangler
# Run locally with hot reload
npm run dev:workerModelo de seguridad
El servidor nunca almacena claves API — las claves se pasan por solicitud mediante encabezado
Los usuarios solo acceden a sus propios datos — cada solicitud usa la propia clave del usuario
Accesible públicamente — cualquiera puede usar el servidor, pero necesitan su propia cuenta de Lunch Money
Esto es similar a cómo funcionan las pasarelas de API públicas: la infraestructura es compartida, pero las credenciales son por usuario.
Ejemplos de uso
Una vez configurado, puedes hacer preguntas a tu asistente de IA como:
"Muéstrame mis gastos por categoría este mes"
"¿Cuál fue mi mayor gasto la semana pasada?"
"Categoriza todas mis transacciones sin categoría de marzo"
"Crea una nueva categoría llamada 'Ingresos Freelance'"
"¿Cuánto gasté en comestibles en el primer trimestre?"
"Lista todas mis suscripciones recurrentes"
Desarrollo
Modo stdio local (para Cursor, Claude Desktop)
# Install dependencies
npm install
# Run in development mode with hot reload
npm run dev
# Build for production
npm run build
# Type check without emitting
npm run typecheck
# Test with MCP Inspector
npm run inspectModo Cloudflare Workers (para acceso HTTP remoto)
# Build the Worker
npm run build
# Run locally with Wrangler
npm run dev:worker
# Deploy to production
npm run deployEstructura del proyecto
src/
├── index.ts # MCP server entry point (stdio mode)
├── worker.ts # Cloudflare Workers entry point (HTTP mode)
├── client.ts # Lunch Money API client
├── types.ts # TypeScript type definitions
├── tool-utils.ts # Shared tool utilities
└── tools/ # Individual tool implementations
├── user.ts
├── categories.ts
├── transactions.ts
├── assets.ts
├── plaid.ts
├── budgets.ts
├── recurring.ts
└── tags.tsModos de despliegue
Modo | Transporte | Caso de uso | Punto de entrada |
Local | stdio | Cursor, Claude Desktop |
|
Cloudflare Workers | Streamable HTTP | Acceso remoto, clientes web |
|
Ambos modos comparten las mismas implementaciones de herramientas y cliente API.
Seguridad
Protección de la clave API
Nunca subas tu clave API. El archivo
.envestá en.gitignorepor esta razón.Almacena tu clave en variables de entorno o archivos de configuración MCP seguros.
Si tu clave queda expuesta, revócala inmediatamente en Desarrolladores de Lunch Money y genera una nueva.
Privacidad de datos
Este servidor actúa como un proxy entre tu asistente de IA y Lunch Money.
Tus datos financieros se procesan de acuerdo con la política de privacidad de Lunch Money.
Los mensajes de error se desinfectan para evitar la divulgación accidental de información.
Permisos
La clave API que proporcionas determina qué acciones puede realizar el servidor MCP. Las claves API de Lunch Money pueden:
Leer todos tus datos financieros
Crear, actualizar y eliminar transacciones
Modificar categorías y presupuestos
Activar sincronizaciones de Plaid
Referencia de la API
Este servidor MCP utiliza la API v1 de Lunch Money.
Límites de tasa
La API de Lunch Money tiene límites de tasa. El servidor MCP pasará cualquier error de límite de tasa de la API. Si encuentras un límite de tasa, espera unos minutos antes de volver a intentarlo.
Manejo de errores
El servidor maneja los errores de la API de Lunch Money y los devuelve como errores de herramientas MCP. Algunas notas:
Lunch Money a veces devuelve errores lógicos como respuestas HTTP 200; estos se normalizan en errores adecuados
El servidor desinfecta los mensajes de error para eliminar información potencialmente sensible
Los detalles completos del error se registran en stderr para depuración
Solución de problemas
Error "Missing LUNCH_MONEY_API_KEY"
La variable de entorno LUNCH_MONEY_API_KEY no está configurada. Revisa tu configuración MCP y asegúrate de que la clave esté configurada correctamente.
Error "Unauthorized"
Tu clave API puede ser inválida o haber sido revocada. Verifica tu clave en https://my.lunchmoney.app/developers
Las transacciones no aparecen
Si usas cuentas conectadas a Plaid, es posible que necesites activar una sincronización:
Usa la herramienta
trigger_plaid_fetchpara poner en cola una sincronización en segundo planoTen en cuenta que esto solo pone en cola el trabajo; puede tardar unos minutos en que aparezcan las transacciones
Contribución
¡Las contribuciones son bienvenidas! Por favor, siéntete libre de enviar un Pull Request.
Haz un fork del repositorio
Crea tu rama de características (
git checkout -b feature/amazing-feature)Confirma tus cambios (
git commit -m 'feat: add amazing feature')Empuja a la rama (
git push origin feature/amazing-feature)Abre un Pull Request
Licencia
Este proyecto está bajo la Licencia ISC; consulta el archivo LICENSE para más detalles.
Reconocimientos
Construido con el SDK de TypeScript del Protocolo de Contexto de Modelo
Impulsado por Lunch Money
Soporte
Para problemas con este servidor MCP, por favor abre un issue en GitHub
Para preguntas sobre la API de Lunch Money, consulta la documentación de la API de Lunch Money
Para preguntas sobre el protocolo MCP, consulta la documentación de MCP
Descargo de responsabilidad: Este es un proyecto comunitario no oficial. No está afiliado ni respaldado por Lunch Money.
Available Tools
15 toolscreate_assetC
Create a manually managed asset in Lunch Money.
| Name | Required | Description | Default |
|---|---|---|---|
| type_name | Yes | ||
| subtype_name | No | ||
| name | Yes | ||
| display_name | No | ||
| balance | Yes | ||
| balance_as_of | No | ||
| currency | No | ||
| institution_name | No | ||
| closed_on | No | ||
| exclude_transactions | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. The single sentence only states the action, omitting any details about side effects, required permissions, rate limits, or response behavior. This is critically insufficient for a creation tool.
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 a single, grammatically correct sentence. However, it is too brief to be useful; conciseness should not come at the cost of essential information. It could be expanded while remaining concise.
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 tool's complexity (10 parameters, no output schema, and no annotations), the description is extremely incomplete. It fails to explain the concept of a 'manually managed asset', how it fits into the Lunch Money system, or what the return value would be. The agent would struggle to use this tool correctly.
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 10 parameters with 0% schema description coverage, meaning the names and types are the only clues. The description adds no explanation of parameter meanings, constraints, or relationships. For example, 'balance' is required but its format or default currency is not clarified.
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 verb ('create') and the resource ('manually managed asset'), and it distinguishes from sibling tools like 'create_category' which deal with different entities. However, it could be more specific about what constitutes a 'manually managed asset' in Lunch Money.
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 provides no guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or scenarios where it should not be used. This lack of context forces the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_categoryC
Create a new Lunch Money category.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| description | No | ||
| is_income | No | ||
| exclude_from_budget | No | ||
| exclude_from_totals | No | ||
| archived | No | ||
| group_id | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states 'Create a new...', which implies a write operation but does not mention side effects, authentication needs, or whether the operation is idempotent. For a mutation tool, this is minimal transparency.
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 a single, concise sentence that immediately states the purpose. It is front-loaded and efficient, with no extraneous words. However, it is too brief and sacrifices informativeness for brevity.
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 tool's complexity (7 parameters, no output schema, no annotations), the description is incomplete. It does not explain how parameters like 'group_id' or 'archived' affect the behavior, nor does it describe the return value or success indicators. More context is needed for effective use.
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 7 parameters with 0% description coverage, meaning the description adds no explanation for any parameter. The description does not compensate for the lack of schema descriptions. It does not clarify the meaning of 'is_income', 'exclude_from_budget', etc., which are non-obvious. The baseline is low due to low 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 action ('Create') and the resource ('a new Lunch Money category'), specifying the verb and object. It distinguishes from sibling tools like 'update_category' and 'get_categories' by implying the creation operation. However, it lacks additional context such as the domain or scope.
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 provides no guidance on when to use this tool versus alternatives. There is no mention of prerequisites, such as requiring an existing group_id, or when to use 'update_category' instead. The name and siblings imply a create operation, but no explicit context is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_transactionC
Create one or more Lunch Money transactions.
| Name | Required | Description | Default |
|---|---|---|---|
| transactions | Yes | ||
| apply_rules | No | ||
| skip_duplicates | No | ||
| check_for_recurring | No | ||
| debit_as_negative | No | ||
| skip_balance_update | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description fails to disclose any behavioral traits (e.g., idempotency, duplicate handling, balance update effects) beyond what is minimally implied by 'Create'. No annotations are present to compensate.
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 extremely concise (one sentence) and front-loaded with the purpose. However, it lacks any structure or additional sections, which is acceptable given the single sentence.
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 complexity of the input schema (many parameters, nested objects) and the absence of annotations and output schema, the description is severely incomplete. It does not explain return values, error cases, or any behavioral details.
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?
Schema description coverage is 0%. The description adds no meaning to the many parameters, such as apply_rules, debit_as_negative, or skip_duplicates, leaving their semantics entirely to the schema.
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 verb 'Create' and the resource 'one or more Lunch Money transactions', which distinguishes it from sibling tools like update_transaction and get_transactions.
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?
No guidance is provided on when to use this tool versus alternatives such as update_transaction, nor are there any prerequisites or constraints mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_assetsARead-only
List manually managed Lunch Money assets.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description's minimal addition of 'manually managed' provides some extra context about the type of assets, but it doesn't contradict annotations or add significant behavioral traits.
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?
Single short sentence with no waste; perfectly front-loaded and to the point.
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?
For a simple listing tool with no parameters and a readOnly annotation, the description provides adequate context, including the asset type (manually managed). No output schema exists, but the tool's behavior is straightforward.
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?
Input schema has no parameters and is fully covered (100%). Description adds value by specifying 'manually managed', which clarifies the scope beyond the empty schema.
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?
Description uses specific verb 'List' and clearly identifies the resource as 'manually managed Lunch Money assets', distinguishing it from siblings like get_plaid_accounts and create_asset.
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?
No explicit guidance on when to use or when not to use this tool versus alternatives. However, the purpose is clear enough that an agent can infer it's for listing only manual assets, not Plaid accounts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_budgetsARead-only
Get Lunch Money budgets and spending for a date range.
| Name | Required | Description | Default |
|---|---|---|---|
| start_date | Yes | ||
| end_date | Yes | ||
| currency | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description adds that it returns both budgets and spending, providing context beyond the annotation. No contradictions.
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?
A single, front-loaded sentence with no wasted words. It is concise but could benefit from slightly more detail without sacrificing brevity.
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?
The description covers purpose and basic output, but lacks parameter explanations and output schema details. For a 3-parameter tool with no output schema, it provides adequate but not comprehensive context.
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?
Schema coverage is 0%: the description does not explain any parameter. While 'date range' hints at start_date/end_date, it omits details on format, optional currency, and usage.
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 'Get' and the resource 'Lunch Money budgets and spending', specifying a date range. It effectively distinguishes from sibling tools like upsert_budget, which is for modifications.
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 implies use when retrieving budget data for a date range but provides no explicit guidance on when to avoid this tool or mention alternatives like upsert_budget.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_categoriesARead-only
List Lunch Money categories in flattened or nested form.
| Name | Required | Description | Default |
|---|---|---|---|
| format | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, so description's value is limited. It adds the format choice but lacks details on response structure, pagination, or ordering.
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?
Single sentence, front-loaded with verb and resource, no unnecessary words. Highly efficient.
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?
For a simple read-only list tool with one optional enum parameter, the description covers the core function and parameter. Lacks mention of output structure, but adequate given simplicity and lack of output schema.
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 single parameter 'format' has an enum, and the description explains its two values ('flattened or nested'), adding meaning beyond the schema (which has 0% description 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 verb 'List' and the resource 'Lunch Money categories', and distinguishes its output format options ('flattened or nested') from sibling tools like create_category or update_category.
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?
No guidance on when to use this tool versus similar list tools (e.g., get_assets, get_tags). No mention of use cases, limitations, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_plaid_accountsARead-only
List Lunch Money Plaid-connected accounts.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, and the description adds no further behavioral details (e.g., data freshness, pagination, or authentication requirements). It simply repeats the read-only nature implied by the annotation.
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 a single, clear sentence with no wasted words. It is concise but could benefit from a bit more detail without becoming verbose.
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?
For a parameterless list tool, the description is adequate but lacks context about potential prerequisites (e.g., Plaid link requirement) or relationship to sibling tools like trigger_plaid_fetch. No output schema exists, but the simplicity of the tool reduces the need for extensive documentation.
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?
There are no parameters in the input schema, so the description does not need to elaborate on parameter meaning. The baseline is 4 for zero-parameter tools.
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 uses the specific verb 'List' and identifies the resource as 'Lunch Money Plaid-connected accounts,' clearly distinguishing it from sibling tools like get_assets or get_categories.
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 does not provide explicit usage guidance, such as when to use this tool versus alternatives like trigger_plaid_fetch. The purpose is clear, but no context on prerequisites or limitations is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_recurring_itemsARead-only
Get Lunch Money recurring items for the current or specified month range.
| Name | Required | Description | Default |
|---|---|---|---|
| start_date | No | ||
| end_date | No | ||
| debit_as_negative | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark this as readOnlyHint=true, and the description aligns with a read operation. Beyond that, no additional behavioral traits (e.g., rate limits, data freshness) are disclosed. The description adds minimal extra context.
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 a single sentence of 12 words, front-loaded with the key action and resource. Every word earns its place with 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 tool has 3 parameters and no output schema, the description covers the core purpose but omits details on the debit_as_negative parameter and response format. It is adequate for low complexity but not fully complete.
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?
Schema description coverage is 0% with 3 parameters. The description hints at start_date/end_date via 'month range' but does not explain debit_as_negative or provide format details. It fails to compensate for low 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 verb 'Get' and resource 'Lunch Money recurring items' with scope 'current or specified month range', distinguishing it clearly from sibling tools like get_transactions and get_budgets.
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 implies usage for month ranges but provides no explicit guidance on when to use this tool versus alternatives such as get_transactions or get_budgets. No exclusions or comparison are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_tagsARead-only
List all Lunch Money tags.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, confirming it's a read operation. The description adds the scope 'all', which is useful context beyond annotations.
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?
One sentence of four words, perfectly front-loaded and without any wasted 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?
While the description is adequate for a simple list tool with no parameters, it lacks information about the return format or fields of the tags. Without an output schema, the description should provide more detail.
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?
No parameters exist in the schema (100% coverage), so baseline is 4. The description does not need to add parameter information.
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 uses a specific verb 'List' and resource 'tags', clearly stating it returns all tags. This distinguishes it from sibling tools that deal with other resources.
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?
No explicit guidance on when to use versus alternatives. Since there are no sibling tag tools, usage is implied, but no exclusions or when-not-to-use are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_transactionsCRead-only
Get Lunch Money transactions with optional filters.
| Name | Required | Description | Default |
|---|---|---|---|
| tag_id | No | ||
| recurring_id | No | ||
| plaid_account_id | No | ||
| category_id | No | ||
| asset_id | No | ||
| is_group | No | ||
| status | No | ||
| start_date | No | ||
| end_date | No | ||
| debit_as_negative | No | ||
| pending | No | ||
| offset | No | ||
| limit | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
While annotations indicate readOnlyHint=true (safe read), the description does not add any behavioral details beyond the obvious. It omits information about pagination, data format, or potential limits.
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 one sentence and concise, but it is too minimal for the complexity of 13 parameters. It is front-loaded but lacks useful structure or breakdown.
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 tool has 13 optional parameters and no output schema, the description does not provide enough context about typical usage, required constraints (e.g., date range), or how filtering works. The agent might miss important behaviors like pagination defaults.
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?
Schema description coverage is 0%, and the description only says 'optional filters' without explaining any of the 13 parameters. The agent receives no additional meaning over parameter names, some of which (e.g., debit_as_negative, is_group) are not self-explanatory.
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 verb 'Get' and the resource 'Lunch Money transactions', and mentions optional filters. It is unambiguous and distinguishes from sibling tools like create_transaction or update_transaction by its name and verb.
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?
No guidance is provided on when to use this tool vs. alternatives (e.g., create_transaction for adding, update_transaction for modifying). The agent must infer from context or tool names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_userARead-only
Get information about the Lunch Money user connected to the configured API key.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint true. The description confirms it's a read operation without adding behavioral details beyond that. It does not specify what specific information is returned or any side effects.
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?
Single sentence that is clear and front-loaded. No unnecessary words or repetition.
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?
The description lacks detail about the return structure. With no output schema, the description should elaborate on what 'information' is returned. It is minimally complete but not comprehensive.
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 zero parameters, and schema coverage is 100%. The description does not need to add parameter semantics. Baseline score of 4 applies.
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 it retrieves information about the Lunch Money user. The verb 'Get' and resource 'information about the Lunch Money user' are specific, and no sibling tool overlaps in purpose.
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?
No explicit guidance on when or when not to use this tool. Since there are no similar siblings, the usage context is implied, but the description does not provide any prerequisites or context for invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
trigger_plaid_fetchC
Trigger a Lunch Money fetch for eligible Plaid accounts. This queues a background fetch job.
| Name | Required | Description | Default |
|---|---|---|---|
| start_date | No | ||
| end_date | No | ||
| plaid_account_id | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries the burden. It notes the job is queued (async), but does not disclose safety, auth requirements, rate limits, or what happens if a fetch is already in progress.
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?
Two sentences are concise, but the description is too brief for a tool with 3 parameters and no output schema. It could be structured better with a brief parameter explanation.
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 complexity (3 params, no output schema, no annotations), the description lacks details on return value, error handling, or behavior when fetch is already queued. It is incomplete for safe invocation.
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?
Schema has 3 optional parameters with 0% description coverage. The description does not explain any parameter, leaving the agent to guess their purpose (e.g., date range or account filter).
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?
Description clearly states the action (trigger fetch) and target (eligible Plaid accounts). It mentions queuing a background job, which adds context. However, it does not define 'eligible', which could confuse the agent.
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?
No guidance on when to use this tool versus alternatives. There is no mention of prerequisites (e.g., account must be linked) or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
update_categoryC
Update an existing Lunch Money category.
| Name | Required | Description | Default |
|---|---|---|---|
| category_id | Yes | ||
| name | No | ||
| description | No | ||
| is_income | No | ||
| exclude_from_budget | No | ||
| exclude_from_totals | No | ||
| archived | No | ||
| group_id | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It only says 'update' without disclosing return behavior, idempotency, or authentication requirements.
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 a single concise sentence, but it is too brief and lacks any structuring (e.g., sections, bullet points).
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 8 parameters and no output schema, the description is severely incomplete. It fails to explain what the tool returns or any side effects.
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?
Schema description coverage is 0%, and the description adds no meaning to any of the 8 parameters. Parameters are completely undocumented.
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 verb 'update' and the resource 'category', distinguishing it from create_category and get_categories. However, it lacks specifics on which fields can be updated, but the purpose is unambiguous.
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?
No guidance on when to use this tool versus alternatives like create_category. No conditions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
update_transactionC
Update a Lunch Money transaction or split it into multiple child transactions.
| Name | Required | Description | Default |
|---|---|---|---|
| transaction_id | Yes | ||
| transaction | No | ||
| split | No | ||
| debit_as_negative | No | ||
| skip_balance_update | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but does not disclose whether updates are partial or full, what happens to existing data, balance implications, or the behavior of splitting. This is a significant gap for a mutation tool.
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 a single sentence, which is concise but lacks structure to cover both operations (update and split). It is adequately short but sacrifices necessary detail.
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 complex input schema and no output schema, the description is severely incomplete. It does not explain return values, error handling, or behavioral details essential for effective use.
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?
Schema description coverage is 0%, and the description provides no explanation of parameters. The complex nested objects 'transaction' and 'split' are completely undocumented, leaving the agent without guidance on how to structure the input.
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 ('Update') and the resource ('a Lunch Money transaction'), and includes the special capability ('split it into multiple child transactions'). This differentiates it from siblings like create_transaction and get_transactions effectively.
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?
No guidance is provided on when to use this tool versus alternatives, nor when splitting is appropriate. There are no prerequisites or contextual conditions mentioned, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
upsert_budgetC
Create or update a Lunch Money budget entry for a category and month.
| Name | Required | Description | Default |
|---|---|---|---|
| start_date | Yes | ||
| category_id | Yes | ||
| amount | Yes | ||
| currency | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It only states 'Create or update', implying a write operation, but provides no details on side effects (e.g., overwriting existing budgets), return values, or required permissions. Behavioral traits are severely under-disclosed.
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 a single concise sentence that immediately conveys the core purpose. It is front-loaded with the action and resource. However, it lacks any structure (e.g., sections) that could improve scannability for an AI agent.
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 no output schema, the description should at least hint at return format or behavior. It mentions 'budget entry for a category and month' but doesn't confirm that start_date should be the first day of the month or that category_id comes from get_categories. The presence of sibling tools like get_budgets for reading is not referenced. Completeness is low.
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?
Schema description coverage is 0%, yet the description adds no parameter information. It fails to explain what start_date, category_id, amount, or currency represent or their constraints (e.g., start_date should be first of month). The description adds zero value beyond the raw schema.
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 verb 'Create or update' and the resource 'Lunch Money budget entry', and specifies the context 'for a category and month'. This distinguishes it from sibling tools like create_category or get_budgets, which involve different resources or actions.
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?
No guidance is provided on when to use this tool versus alternatives or when not to use it. For example, it doesn't clarify that the upsert replaces existing budgets for the same category and month, or that get_budgets should be used for reading. The description lacks any comparative context.
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.
15 tool updates
v1.0.0- First observed
create_asset - First observed
create_category - First observed
create_transaction - First observed
get_assets - First observed
get_budgets - First observed
get_categories - First observed
get_plaid_accounts - First observed
get_recurring_items - First observed
get_tags - First observed
get_transactions - First observed
get_user - First observed
trigger_plaid_fetch - First observed
update_category - First observed
update_transaction - First observed
upsert_budget
TDQS
Scored across 15 tools
Each tool targets a distinct resource or action, with clear separation between asset, category, transaction, budget, account, recurring item, tag, and user operations. No overlapping functionality.
All tools follow a consistent verb_noun pattern (e.g., create_asset, get_transactions, update_category), using the same set of verbs (create, get, update, upsert, trigger) throughout.
With 15 tools, the server covers the core aspects of personal finance management without being overloaded or underdeveloped. Each tool has a clear purpose.
The server provides create, read, and update operations for several resources, but lacks delete operations for all resources and missing update for assets and recurring items. Tags only have a get operation, leaving significant gaps in the lifecycle.
Maintenance
Related MCP Connectors
Read-only Lunch Money accounts, transactions, categories and budgets. Unofficial connector.
Personal-finance workspace for AI agents: accounts, spending, budgets, goals, and investments.
- BankSyncOAuthio.banksync
Connect AI agents to bank accounts, transactions, balances, and investments.
- Era ContextOAuthapp.era
Personal finance, bank account, and shared memory connector for Claude, ChatGPT, Gemini Spark & more
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