mern-mcp es un servidor de código abierto del Protocolo de Contexto de Modelos (MCP) para generar recursos CRUD completos del stack MERN dentro de un código existente, con soporte de configuración directa tanto para Claude Code como para Codex CLI. Genera modelos de MongoDB y Mongoose, servicios y rutas de Express, módulos de cliente React y la conexión necesaria para integrar nuevos recursos en una aplicación real con un flujo de trabajo más seguro de vista previa antes de aplicar.
Si buscas un servidor MCP para desarrollo con el stack MERN, un generador de CRUD para MongoDB Express React Node.js, un generador de plantillas de Mongoose y Express, o un generador de paneles de administración React que funcione con asistentes de codificación con IA, este repositorio está creado exactamente para ese caso de uso.
Índice: Por qué es útil · Archivos generados · Instalación · Configuración · Claude Code · Codex CLI · Docker · Herramientas MCP · Ejemplo · Estilos de proyecto · Lenguaje natural · Flujo de vista previa · Para quién es
Related MCP server: MCP Terminal & Git Server
Los equipos normalmente no necesitan otro generador de código genérico. Necesitan una herramienta MCP local que pueda inspeccionar un proyecto, seguir una estructura de carpetas existente, crear fragmentos CRUD repetibles y evitar escrituras a ciegas. mern-mcp se centra en ese flujo de trabajo práctico.
Incluso si ya tienes MCPs para Next.js, Node.js o MongoDB, esas herramientas suelen ayudar a nivel de framework o base de datos. mern-mcp es útil porque maneja el flujo de trabajo completo del recurso en un solo lugar: modelo, servicio, controlador, rutas, validadores, API de cliente, hooks, formularios, vistas de lista, vistas de detalle y parches de integración. En lugar de pedirle a un asistente que conecte cada capa por separado, un desarrollador puede generar un fragmento CRUD completo en una sola pasada, revisar el plan y pasar más rápido a la lógica de negocio. Esto reduce el trabajo repetitivo de configuración, disminuye los pasos de integración omitidos y hace que el desarrollo full-stack diario sea mucho menos tedioso.
Es especialmente útil cuando quieres:
generar una API CRUD MERN y una interfaz React a partir de un esquema de recurso
generar modelos de Mongoose, controladores de Express, servicios, rutas y validadores
generar formularios React, vistas de lista, vistas de detalle, hooks, tipos compartidos y módulos de API
permitir que un asistente de codificación compatible con MCP cree recursos dentro de tu propio repositorio
previsualizar los cambios de archivos antes de aplicarlos
gestionar recursos generados a lo largo del tiempo con flujos de agregar campo y eliminar
soportar monorepos o proyectos separados de servidor y cliente
mern-mcpPara cada recurso, mern-mcp puede generar:
archivo de modelo del servidor
archivo de servicio del servidor
archivo de controlador del servidor
archivo de rutas del servidor
archivo de validador del servidor cuando la validación está habilitada
archivo de middleware de autenticación cuando la autenticación JWT está habilitada
archivo de tipos compartidos del cliente
módulo de API del cliente
hook de datos del cliente
componente de formulario del cliente
componente de lista del cliente
componente de detalle del cliente
Las rutas generadas típicas se ven así:
server/models/product.model.ts
server/services/product.service.ts
server/controllers/product.controller.ts
server/routes/product.routes.ts
server/validators/product.validator.ts
client/types/product.types.ts
client/api/product.api.ts
client/hooks/useProduct.ts
client/components/ProductForm.tsx
client/components/ProductList.tsx
client/components/ProductDetail.tsxEl planificador también puede parchear archivos existentes cuando detecta patrones compatibles:
montar nuevas rutas de Express en un archivo de entrada del servidor
registrar nuevas rutas en un archivo de React Router
registrar reducers en un store de Redux cuando la forma del store detectada es compatible
npm install
npm run buildEjecuta el servidor MCP compilado contra un proyecto MERN objetivo:
node dist/index.js --project-root /absolute/path/to/target-projectPara desarrollo local:
npm run dev -- --project-root /absolute/path/to/target-projectCrea mern-mcp.config.json en la raíz del proyecto objetivo.
Ejemplo para un proyecto monorepo TypeScript que usa React Query:
{
"structure": "monorepo",
"language": "typescript",
"reactStack": "react-query",
"validation": "zod",
"auth": "none",
"rbac": false,
"paths": {
"serverRoot": "./server",
"clientRoot": "./client",
"serverEntry": "index.ts",
"clientRouter": "router.tsx"
}
}Ejemplo para aplicaciones separadas de cliente y servidor con Redux y autenticación JWT:
{
"structure": "separate",
"language": "typescript",
"reactStack": "redux",
"validation": "both",
"auth": "jwt",
"paths": {
"serverRoot": "./server",
"clientRoot": "./client",
"modelsDir": "src/models",
"servicesDir": "src/services",
"controllersDir": "src/controllers",
"routesDir": "src/routes",
"validatorsDir": "src/validators",
"middlewareDir": "src/middleware",
"componentsDir": "src/components",
"hooksDir": "src/hooks",
"apiDir": "src/api",
"typesDir": "src/types",
"serverEntry": "src/index.ts",
"clientRouter": "src/router.tsx",
"clientStore": "src/store.ts"
}
}Todos los directorios de artefactos se pueden sobrescribir mediante paths.
Instala las dependencias y compila este repositorio:
npm install
npm run buildCrea mern-mcp.config.json en el proyecto MERN objetivo que quieras generar.
Añade el servidor MCP a Claude Code:
claude mcp add mern-mcp -- node /absolute/path/to/mern-mcp/dist/index.js --project-root /absolute/path/to/projectConfirma que el servidor está disponible en Claude Code.
Empieza con preview_scaffold antes de usar scaffold_resource en modo aplicar.
Instala las dependencias y compila este repositorio:
npm install
npm run buildCrea mern-mcp.config.json en el proyecto MERN objetivo que quieras generar.
Añade el servidor MCP a Codex CLI:
codex mcp add mern-mcp --command node --args /absolute/path/to/mern-mcp/dist/index.js --project-root /absolute/path/to/projectConfirma que el servidor MCP aparece en Codex.
Empieza con preview_scaffold, inspecciona el plan generado y luego reutiliza el previewHash devuelto para el modo aplicar.
Puedes ejecutar mern-mcp en Docker si no quieres instalar Node.js directamente en el host.
Construye la imagen desde este repositorio:
docker build -t mern-mcp .Asegúrate de que el proyecto MERN objetivo contenga mern-mcp.config.json.
Ejecuta el contenedor y monta el proyecto objetivo en él:
docker run --rm -i \
-v /absolute/path/to/target-project:/workspace \
mern-mcp \
--project-root /workspaceSi quieres registrar el servidor en contenedor en un cliente MCP, usa Docker como comando y pasa los mismos argumentos.
Forma de ejemplo:
docker run --rm -i -v /absolute/path/to/target-project:/workspace mern-mcp --project-root /workspaceEl servidor registra actualmente estas herramientas:
preview_scaffold
scaffold_resource
list_resources
add_field
delete_resource
preview_scaffoldEjecuta una simulación de generación e inspecciona el plan de escritura generado antes de cambiar archivos.
scaffold_resourcePrevisualiza o aplica una generación CRUD MERN completa para un recurso.
list_resourcesLista los recursos gestionados por el manifiesto y, opcionalmente, escanea el proyecto en busca de recursos no gestionados.
add_fieldPrevisualiza o aplica un nuevo campo en un recurso generado existente.
delete_resourcePrevisualiza o aplica la eliminación de un recurso generado y elimina su registro del manifiesto.
Para scaffold_resource, add_field y delete_resource, las entradas importantes son:
mode: "preview" o "apply"
previewHash: requerido en modo "apply"
conflictStrategy: "abort", "overwrite" o "skip"
Ejemplo de solicitud de vista previa para un recurso de producto:
{
"resourceName": "Product",
"fields": [
{ "name": "title", "type": "string", "required": true },
{ "name": "price", "type": "number", "required": true },
{ "name": "inStock", "type": "boolean", "required": false }
],
"mode": "preview"
}Después de previsualizar, reutiliza el previewHash devuelto para el modo aplicar.
mern-mcp admite generación de código MERN configurable en estas dimensiones:
estructura del proyecto: monorepo o separate
lenguaje: typescript o javascript
stack de datos React: plain, react-query, redux o axios
validación: zod, express-validator, both o none
autenticación: jwt o none
También admite rutas configurables, para que puedas apuntar la generación a directorios personalizados como src/models, src/routes, src/components o src/store.ts.
Puedes generar un recurso de dos maneras:
Pasar un esquema de campos explícito.
Pasar una descripción en lenguaje natural y dejar que el planificador infiera los campos.
Ejemplo de entrada en lenguaje natural:
a blog post with title, body, author, tagsEse estilo de entrada se analiza en una estructura de recurso donde términos como author pueden convertirse en una referencia objectId y términos como tags pueden convertirse en arrays de cadenas.
Los tipos de campo compatibles incluyen:
string
number
boolean
date
objectId
Las sugerencias de widgets de interfaz compatibles incluyen:
text
textarea
number
checkbox
date
select
multiselect
tags
Una de las partes más sólidas de este repositorio es el contrato de vista previa/aplicación.
el modo preview devuelve el plan, los artefactos, las acciones de integración, los conflictos y un previewHash determinista
el modo apply requiere el previewHash correspondiente
los conflictos con archivos no gestionados se pueden manejar con abort, overwrite o skip
las rutas de los recursos generados se rastrean en .mern-mcp-manifest.json
Esto brinda a las herramientas de IA y a los operadores humanos una forma más controlada de generar código sin sobrescribir silenciosamente trabajo no relacionado.
mern-mcp es una buena opción para:
desarrolladores del stack MERN que quieren una generación de recursos más rápida
flujos de trabajo de codificación asistida por IA que usan MCP
agencias que crean paneles de administración repetidos y back offices CRUD
equipos de startups que lanzan herramientas internas o paneles de control SaaS
equipos de TypeScript y JavaScript que mantienen convenciones consistentes
desarrolladores que quieren generación e integración, no solo plantillas de código sueltas
La gente suele buscar proyectos como este con frases como:
servidor MCP para el stack MERN
generador de CRUD para el stack MERN
generador de andamiaje para MongoDB Express React Node
generador de modelos Mongoose
generador de plantillas de API Express
generador de CRUD con React Query
generador de andamiaje CRUD con Redux
generador de código IA para aplicaciones MERN
herramientas MCP locales para JavaScript full-stack
andamiaje CRUD TypeScript full-stack
Esas frases son relevantes aquí porque este servidor genera directamente esos artefactos e integraciones.
Si alguien busca una herramienta de andamiaje para el stack MERN desde EE. UU., Canadá, Reino Unido, Europa, Oriente Medio, India, Bangladés, Pakistán, Singapur o Australia, la respuesta sigue siendo la misma: mern-mcp se ejecuta localmente en tu propio proyecto y no está vinculado a una región de nube específica ni a una plataforma alojada.
Eso lo hace adecuado para equipos de ingeniería distribuidos, agencias remotas, equipos de startups, desarrolladores independientes y empresas de producto que trabajan desde ciudades como Nueva York, Toronto, Londres, Berlín, Dubái, Bengaluru, Daca, Singapur o Sídney, siempre que el proyecto use Node.js y un cliente compatible con MCP.
Este repositorio no es solo un volcado de plantillas. Contiene:
un servidor MCP ejecutable
esquemas de entrada tipados con Zod
resolución de rutas de proyecto configurable
parcheadores de integración basados en AST para el registro del servidor y del cliente
gestión de recursos respaldada por manifiesto
flujos de vista previa, aplicar, agregar campo, listar y eliminar
pruebas y cobertura de humo para el ciclo de vida principal
Esa combinación es directamente relevante para búsquedas sobre generación de código MERN, herramientas MCP, andamiaje CRUD, generación de rutas Express, generación de modelos Mongoose, ayudas CRUD con React Query, andamiaje Redux y automatización full-stack con TypeScript.
npm run check
npm test
npm run build
npm run smokeMIT
Preview or apply a new field on an existing manifest-managed resource.
| Name | Required | Description | Default |
|---|---|---|---|
| mode | No | preview | |
| field | Yes | ||
| previewHash | No | ||
| resourceName | Yes | ||
| conflictStrategy | No | abort |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full transparency burden, yet it only reveals the existence of two behavioral modes ('Preview or apply'). It fails to disclose the two-phase handshake workflow (preview returns a previewHash that apply requires), the implications of conflictStrategy values including the potentially destructive 'overwrite', or any safety caveats about modifying manifest-managed resources. The single sentence is the barest outline of behavior.
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 sentence is economically constructed, front-loading the action verb and fitting meaningful scoping in a single readable clause. However, 'appropriately sized' is questionable — for a tool with this much complexity, one sentence is arguably under-specification rather than genuine conciseness. On pure prose quality it's well-built, but it earns no credit for elegance at the expense of substance.
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?
This tool has a nested field object with ten properties, a two-phase preview/apply workflow, a conflict resolution strategy with potentially destructive values, a required previewHash handoff, and zero annotations or output schema describing any of it. The description needed to do significant heavy lifting and performs none of it. An agent cannot learn the workflow or safely invoke apply mode from this text alone.
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?
With schema description coverage at 0%, the description was obligated to compensate but names no parameters directly. 'Existing manifest-managed resource' loosely implies resourceName, but nothing explains the field structure, the preview/apply handoff via previewHash, or the conflictStrategy semantics. All five parameters, including the nested field object with its ten sub-properties, go entirely unexplained.
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 has a specific verb-object construction ('Preview or apply a new field') and a clear resource target ('an existing manifest-managed resource'). The 'manifest-managed' qualifier usefully distinguishes this from scaffolding new resources. However, differentiation from siblings like preview_scaffold or scaffold_resource is left implicit, not stated.
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 offers no explicit guidance on when to choose this tool over alternatives such as scaffold_resource or preview_scaffold. The 'preview or apply' phrasing hints at a workflow — run preview first, then apply — but never states that the preview output is needed as subsequent input (previewHash) or when each mode is appropriate. An agent must infer the intended usage pattern from the schema.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Preview or apply deletion for a manifest-managed generated resource.
| Name | Required | Description | Default |
|---|---|---|---|
| mode | No | preview | |
| previewHash | No | ||
| resourceName | Yes | ||
| conflictStrategy | No | abort |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It does reveal the dual-mode nature (preview vs. apply), which is useful, but it omits critical information about a destructive operation, such as irreversibility, cascading effects, idempotency, or whether it requires confirmation. The agent is left unaware of the consequences of 'apply' beyond a generic deletion.
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 with no filler. It front-loads the primary action ('Preview or apply deletion') and adds the contextual qualifier. While it could be more detailed, the structure is clean and easily scannable.
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 destructive tool with four parameters and zero annotations, the description is grossly insufficient. It fails to explain the meaning of 'preview' vs. 'apply' in practical terms, what 'conflictStrategy' does, or what happens to dependent resources. An agent cannot safely invoke this tool correctly with the information provided.
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%, so the description must compensate by explaining parameters, but it doesn't. It never defines 'resourceName', 'mode', 'previewHash', or 'conflictStrategy'. The enums and defaults in the schema are uninterpreted, and the description adds no semantic value about how these parameters affect behavior. This is a critical gap.
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 a specific verb ('delete') and resource ('manifest-managed generated resource'), distinguishing it from siblings like scaffold_resource or list_resources. It also introduces the preview/apply dual-mode behavior, which is a distinct attribute. Could be more explicit about the scope, but it's markedly better than a tautology.
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: use 'preview' to simulate deletion and 'apply' to execute it, which gives context but doesn't explicitly state when to choose this over alternatives or when not to use it. It doesn't mention any preconditions, confirmations, or relationship to preview_scaffold, leaving implied usage rather than explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List manifest-managed resources and optionally scan for unmanaged ones.
| Name | Required | Description | Default |
|---|---|---|---|
| includeUnmanaged | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It does convey the read-only listing intent and the optional unmanaged-scan behavior, which is genuinely useful context beyond the name. However, it does not disclose what the scan entails, what the return payload looks like, or what 'unmanaged' means concretely — meaningful gaps given there is 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence with zero filler. The primary purpose leads, and the optional behavior is appended as a second clause. Nothing is wasted and every word earns its place.
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?
Complexity is low — one optional boolean parameter, no output schema, no nested structures. For a simple list tool the description is largely sufficient: it states the main function and the one behavioral toggle. Minor omissions (return format, definition of 'unmanaged') are tolerable against the low complexity, though they keep it from being 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%, so the description must compensate. It partially does: 'optionally scan for unmanaged ones' maps semantically to the includeUnmanaged boolean (which defaults to true), giving the parameter purpose. But the description never names the parameter or explains the true-default implication, leaving the agent to infer the connection. It adds value but does not fully bridge the 0% coverage gap.
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?
States a specific verb ('List') and a precise resource ('manifest-managed resources'), plus an optional secondary behavior ('scan for unmanaged ones'). It is clearly distinguishable from its siblings (scaffold_resource, delete_resource, add_field, preview_scaffold), all of which are mutation tools, so an agent can separate read from write intent immediately.
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 read-versus-mutate distinction against the sibling tools is implied by the verb and resource, but the description never explicitly says 'use this when you need to enumerate resources, not when you need to modify them.' No alternatives are named, and no conditions selecting this tool over another are given. Adequate but left to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Preview the generated files and integration edits for a MERN resource scaffold.
| Name | Required | Description | Default |
|---|---|---|---|
| mode | No | preview | |
| fields | No | ||
| overrides | No | ||
| description | No | ||
| previewHash | No | ||
| resourceName | Yes | ||
| conflictStrategy | No | abort |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. The description says 'Preview' which suggests a read-only operation, but the input schema includes a 'mode' parameter with 'preview' and 'apply' values, indicating this tool can also apply changes. The description is misleading as it claims only preview but the tool supports apply. This is a behavioral gap and borderline contradiction with the schema (not 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?
The description is a single, concise sentence that is easy to parse. It front-loads the verb and resource. It doesn't waste words. However, it omits crucial details about the mode parameter, which would have been valuable, but conciseness itself is good.
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 7 parameters, nested objects, an apply mode that causes mutations, and no output schema, the description is insufficient. An agent needs to know when to use apply vs preview, what the preview output looks like, and how conflictStrategy works. The description only covers a fraction of the complexity.
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%, so the description must compensate for parameter meaning. However, the description does not explain any parameter semantics. It doesn't clarify what 'previewHash' is, what 'conflictStrategy' does, or what 'overrides' affect. The baseline for 0% coverage is low, and the description adds nothing. Score 3 is generous; it could be 2, but the tool purpose is simple enough that resourceName is 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 states a specific verb ('Preview') and resource ('generated files and integration edits for a MERN resource scaffold'). It clearly distinguishes from sibling tools like scaffold_resource (which likely creates), but doesn't explicitly contrast with it. The term 'preview' implies no side effects, which is clear enough.
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 name 'preview_scaffold' and description imply this is for reviewing changes before applying them, but it doesn't explicitly state when to use it versus scaffold_resource or when not to use it. There is no mention of alternatives or conditions. The description implies usage but leaves the decision to the agent inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Generate a full MERN CRUD slice for one resource and either preview or apply the write plan.
| Name | Required | Description | Default |
|---|---|---|---|
| mode | No | preview | |
| fields | No | ||
| overrides | No | ||
| description | No | ||
| previewHash | No | ||
| resourceName | Yes | ||
| conflictStrategy | No | abort |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. The description only says 'Generate a full MERN CRUD slice' and 'preview or apply the write plan'. It does not disclose behavioral details like that applying will create/modify files, potential destructive actions, side effects, or the nature of the write plan. For a tool that can 'apply' changes, this lack of behavioral transparency is a notable gap.
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 conveys the key options (preview/apply) without extra fluff. It is concise and front-loaded with the core action. However, it does take a slight liberty with 'write plan' which is not defined elsewhere.
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 high complexity (7 params, nested objects, no output schema, no annotations), the description is far from complete. It doesn't mention the previewHash, conflictStrategy, or how to get a preview. It also doesn't clarify the relationship with sibling 'preview_scaffold'. A function this complex needs much more guidance on workflow, preconditions, and output expectations.
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%, so the description must compensate for parameter meaning. However, the description does not explain any of the parameters beyond hinting at 'resource' and 'write plan'. With 7 parameters including nested 'fields' and 'overrides', the agent receives very little guidance on what these mean or how to structure them. The enums for mode and conflictStrategy are partially self-explanatory, but the description adds no semantic value.
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 states the verb 'Generate' and resource 'full MERN CRUD slice' for a resource, and distinguishes between preview and apply modes. It is clear about the tool's core purpose. However, it doesn't explicitly differentiate from the sibling tool 'preview_scaffold', which appears to overlap with the preview mode mentioned.
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 by mentioning 'preview or apply the write plan', but it does not explicitly state when to use this tool versus alternatives like 'preview_scaffold'. It lacks guidance on when to choose preview vs apply or how this relates to 'add_field' or 'update_drive' (though siblings include 'list_resources', 'delete_resource', 'add_field'). The context is somewhat clear but no explicit exclusions or alternative routing is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v0.1.0add_fielddelete_resourcelist_resourcespreview_scaffoldscaffold_resourceScored across 5 tools
list_resources, delete_resource, and add_field are clearly distinct, but scaffold_resource already supports previewing or applying a write plan, making preview_scaffold semantically overlapping. Descriptions help clarify intent, but an agent could easily pick the wrong tool for a preview action.
All five tool names follow a verb_noun snake_case pattern: scaffold/list/preview/delete/add + resource/scaffold/field. The only minor variance is singular vs. plural objects (list_resources vs. delete_resource), but no convention mixing occurs.
Five tools is a reasonable scope for managing MERN scaffolds, not bloated. However, preview_scaffold is arguably redundant with scaffold_resource's preview mode, so the set is slightly looser than ideal.
The main lifecycle is covered: scaffold a resource, list resources, add a field, and delete a resource. There is no counterpart to remove or update fields, leaving add_field as a one-way operation and requiring workarounds like delete-and-rescaffold.
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