mern-mcp — это MCP-сервер с открытым исходным кодом для создания CRUD-ресурсов полного MERN-стека в существующей кодовой базе, с прямой поддержкой настройки как для Claude Code, так и для Codex CLI. Он генерирует модели MongoDB и Mongoose, маршруты и контроллеры Express, клиентские модули React и всю обвязку для подключения нового ресурса в реальное приложение с более безопасным рабочим процессом «сначала предпросмотр, потом применение».
Если вы ищете MCP-сервер для разработки на MERN-стеке, генератор CRUD для MongoDB Express React Node, генератор моделей Mongoose и маршрутов Express, конструктор React-админки для работы с AI-ассистентами кодирования, этот репозиторий создан именно для этого.
Оглавление: Зачем полезен этот репозиторий · Что генерирует mern-mcp · Установка · Конфигурация · Claude Code · Codex CLI · Docker · MCP Tools · Пример · Стили проектов · Естественный язык · Безопасный предпросмотр · Для кого этот проект
Related MCP server: MCP Terminal & Git Server
Командам обычно не нужен ещё один типовой генератор кода. Им нужен локальный MCP-инструмент, который может проверить проект, следовать существующей структуре папок, создавать повторяемые CRUD-срезы и избегать слепых записей. mern-mcp сосредоточен на этом практическом рабочем процессе.
Даже если у вас уже есть MCP-клиенты для Next.js, Node.js или MongoDB, эти инструменты обычно помогают на уровне фреймворка или базы данных. mern-mcp полезен тем, что обрабатывает весь путь создания ресурса в одном месте: модель, сервис, контроллер, маршруты, валидаторы, клиентский API, хуки, формы, представления списков, представления деталей и патчи интеграции. Вместо того чтобы просить ассистента соединять каждый слой отдельно, разработчик может создать весь CRUD-срез за один проход, изучить план и перейти к бизнес-логике быстрее. Это сокращает повторяющуюся работу, уменьшает количество пропущенных шагов интеграции и делает повседневную full-stack разработку заметно менее утомительной.
Это особенно полезно, когда нужно:
создать CRUD API и React UI ресурса из схемы
генерировать схемы Mongoose, контроллеры Express, сервисы, маршруты и валидаторы
генерировать React-формы, представления списков, представления деталей, хуки, общие типы и API-модули
позволить MCP-совместимому ассистенту кодирования создавать ресурсы в вашем собственном репозитории
предпросмотр изменений файлов до их применения
управлять сгенерированными ресурсами в течение нескольких лет с помощью процессов add-field/delete
поддерживать монорепозиторий или отдельные проекты сервера и клиента
mern-mcpДля каждого ресурса mern-mcp активирует:
server model file (файл серверной модели)
server service file (файл сервиса?)
server controller file (файл контроллера)
server routes file (файл маршрутов)
server validator file when validating enabled (файл валидатора)
auth middleware file when JWT auth enabled (файл auth-middleware)
client shared types file (файл общих типов)
client API module (API-модуль клиента)
client data hook (клиентский хук данных)
client form component (клиентский компонент формы)
client list component (клиентский компонент списка)
client detail component (клиентский компонент деталей)
Обычные сгенерированные пути выглядят так:
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.tsxПланировщик умеет пропатчивать существующие файлы, когда обнаруживает поддерживаемые паттерны:
монтировать новые Express-маршруты в серверный entry-файл
регистрировать новые маршруты в файле React Router
регистрировать редьюсеры в store Redux, если поддерживается определённая форма store
npm install
npm run buildЗапустите откомпилированный MCP-сервер против целевого MERN-проекта:
node dist/index.js --project-root /absolute/path/to/target-projectДля локальной разработки:
npm run dev -- --project-root /absolute/path/to/target-projectСоздайте mern-mcp.config.json в корне целевого проекта.
Пример для монорепозитория TypeScript-проекта с 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"
}
}Пример для раздельных приложений клиента и сервера с Redux и JWT-аутентификацией:
{
"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"
}
}Все пути артефактов переопределяются через paths.
Установите зависимости и соберите этот репозиторий:
npm install
npm run buildСоздайте mern-mcp.config.json в целевом MERN-проекте.
Добавьте MCP-сервер в Claude Code:
claude mcp add mern-mcp -- node /absolute/path/to/mern-mcp/dist/index.js --project-root /absolute/path/to/projectУбедитесь, что сервер доступен в Claude.
Начните с preview_scaffold, прежде чем использовать scaffold_resource в режиме apply.
Установите зависимости и соберите этот репозиторий:
npm install
npm run buildСоздайте mern-mcp.config.json в целевом MERN-проекте.
Добавьте MCP-сервер в Codex CLI:
codex mcp add mern-mcp --command node --args /absolute/path/to/mern-mcp/dist/index.js --project-root /absolute/path/to/projectУбедитесь, что MCP-сервер указан в Codex.
Начните с preview_scaffold, проверьте сгенерированный план, затем используйте возвращаемый previewHash для режима apply.
Вы можете запустить mern-mcp в Docker, если не хотите устанавливать Node.js прямо на хост.
Соберите образ из этого репозитория:
docker build -t mern-mcp .Убедитесь, что целевой MERN-проект содержит mern-mcp.config.json.
Запустите контейнер и смонтируйте целевой проект внутрь:
docker run --rm -i \
-v /absolute/path/to/target-project:/workspace \
mern-mcp \
--project-root /workspaceЕсли вы хотите зарегистрировать сервер с Dockerized в MCP-клиенте, используйте Docker как команду и укажите те же аргументы.
Пример формы:
docker run --rm -i -v /absolute/path/to/target-project:/workspace mern-mcp --project-root /workspaceСервер в настоящее время регистрирует такие инструменты:
preview_scaffold
scaffold_resource
list_resources
add_field
delete_resource
preview_scaffold (предпросмотр каркаса)Предварительный просмотр схемы и проверка сгенерированного плана записи перед изменением файлов.
scaffold_resource (каркас ресурса)Предпросмотр или применение полного MERN CRUD-подмостков для ресурса.
list_resources (список ресурсов)Перечислить ресурсы, управляемые манифестом, и при желании найти неуправляемые ресурсы в проекте.
add_field (добавить поле)Предпросмотр или применение нового поля к существующему сгенерированному ресурсу.
delete_resource (удалить ресурс)Предпросмотр или применение удаления для созданного ресурса и удалить запись из манифеста.
То же самое для scaffold_resource, add_field, и delete_resource важные входы:
mode: "preview" или "apply"
previewHash (хэш предпросмотра): требуется в режиме "apply"
conflictStrategy (стратегия конфликта): "abort", "overwrite" или "skip"
Пример запроса на предпросмотр ресурса product:
{
"resourceName": "Product",
"fields": [
{ "name": "title", "type": "string", "required": true },
{ "name": "price", "type": "number", "required": true },
{ "name": "inStock", "type": "boolean", "required": false }
],
"mode": "preview"
}После предпросмотра используйте возвращённый preview (предпросмотр) и хэш previewHash для режима apply.
mern-mcp поддерживает настраиваемую генерацию кода MERN по следующим параметрам:
структура проекта: monorepo или separate
язык: typescript или javascript
стек данных React: plain, react-query, redux или axios
валидация: zod, express-validator, both или none
аутентификация: jwt или none
Она также поддерживает настраиваемые пути, поэтому вы можете указать генерацию в пользовательские каталоги, например src/models, src/routes, src/components или src/store.ts.
Вы можете создать ресурс двумя способами:
Передать явную схему полей.
Передать описание на естественном языке и позволить планировщику вывести поля.
Пример ввода на естественном языке:
a blog post with title, body, author, tagsТакой ввод разбирается в структуру ресурса, где такие термины, как author (автор), могут стать ссылкой objectId, а такие термины, как tags, могут стать массивом строк.
Поддерживаемые типы полей:
string
number
boolean
date
objectId
Поддерживаемые виджеты UI:
text
textarea
number
checkbox
date
select
multiselect
tags
Одна из самых сильных сторон этого репозитория — контракт предпросмотра/применения.
Режим preview возвращает план, его артефакты и конфликты по интеграции, а также детерминированный previewHash.
Режим apply требует соответствующего previewHash
Конфликты с неуправляемыми файлами можно обрабатывать через abort, overwrite или skip
пути сгенерированных ресурсов отслеживаются в .mern-mcp-manifest.json
Это даёт ИИ-инструментам и разработчикам более контролируемый способ строить код без беззвучной перезаписи чужих наработок.
mern-mcp — хороший выбор для:
разработчиков MERNMRN-стека, желающих ускорить создание ресурсов
AI-ассистируемых кодинговых процессов, работающих через MCP
агентств, строящих повторяющиеся админ-панели и внутренние CRUD-системы
стартапов, выпускающих внутренние инструменты или SaaS-консоли управления
TypeScript- и JavaScript-команд, сохраняющих единые стандарты
разработчиков, которые хотят генерацию и интеграцию, а не просто сырые шаблоны
Люди часто ищут проекты такого типа по фразам вроде:
MCP-сервер для MERN-стека
MERN CRUD-генератор
MongoDB Express React Node-генератор каркасов
генератор моделей Mongoose
Express API-генератор шаблонов
React Query CRUD-генератор
Redux CRUD-каркас
ИИ-генератор кода для приложений MERN
локальный MCP-инструмент для full-stack JavaScript
TypeScript-каркас CRUD
Эти запросы уместны, потому что сервер напрямую генерирует эти артефакты и интеграции.
Если кто-то ищет инструмент каркаса MERN-стека из США, Канады, Европы, Великобритании, Ближнего Востока, Индии, Бангладеша, Пакистана, Сингапура или Австралии, ответ всё равно один: mern-mcp работает локально в вашем проекте и не привязан к конкретному региону облака или размещённой платформе.
Это подходит для распределённых команд, удалённых агентств, стратап-групп, фрилансеров и продуктовых команд, работающих в таких городах, как Нью-Йорк, Лондон, Берлин, Дубай, Бангалор, Дакка, Сингапур или Сидней, если проект использует Node.js или MCP-совместимый клиент.
Этот репозиторий не просто набор шаблонов. В нём есть:
рабочий MCP-сервер
типизированные входные схемы через Zod
настраиваемое разрешение путей проекта
AST-патчи для регистрации серверов и клиентов
ресурсы управления манифестами
процессы предпросмотра, применения, добавления полей, списка и удаления
тесты и смоук-покрытие основного жизненного цикла
Эта комбинация напрямую релевантна для поисков по генерации кода MERN, инструментам MCP, CRUD-шаблонам, генерации маршрутов Express, генерации моделей Mongoose, CRUD-хелперам React Query, Redux-шаблонам и автоматизации полного цикла 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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