mern-mcp ist ein Open-Source-Model-Context-Protocol-(MCP)-Server zum Erstellen vollständiger MERN-Stack-CRUD-Ressourcen in einer bestehenden Codebasis, mit direkter Einrichtungsunterstützung für Claude Code und Codex CLI. Er generiert MongoDB- und Mongoose-Modelle, Express-Services und -Routen, React-Client-Module und die Verdrahtung, die benötigt wird, um neue Ressourcen mit einem sichereren Vorschau-vor-Anwenden-Workflow in eine echte Anwendung einzubinden.
Wenn Sie nach einem MCP-Server für die MERN-Stack-Entwicklung suchen, einem MongoDB-Express-React-Node.js-CRUD-Generator, einem Mongoose-plus-Express-Boilerplate-Generator oder einem React-Admin-Scaffolder, der mit KI-Codierungsassistenten funktioniert, dann ist dieses Repository genau für diesen Anwendungsfall gebaut.
Inhaltsverzeichnis: Warum nützlich · Generierte Dateien · Installation · Konfiguration · Claude Code · Codex CLI · Docker · MCP-Tools · Beispiel · Projektstile · Natürliche Sprache · Vorschau-Workflow · Für wen
Related MCP server: MCP Terminal & Git Server
Teams brauchen normalerweise keinen weiteren generischen Code-Generator. Sie brauchen ein lokales MCP-Tool, das ein Projekt untersuchen, einer bestehenden Ordnerstruktur folgen, wiederholbare CRUD-Slices erstellen und blinde Schreibvorgänge vermeiden kann. mern-mcp konzentriert sich auf diesen praktischen Workflow.
Selbst wenn Sie bereits MCPs für Next.js, Node.js oder MongoDB haben, helfen diese Tools normalerweise auf Framework- oder Datenbankebene. mern-mcp ist nützlich, weil es den gesamten Ressourcen-Workflow an einer Stelle abwickelt: Modell, Service, Controller, Routen, Validatoren, Client-API, Hooks, Formulare, Listenansichten, Detailansichten und Integrations-Patches. Statt einen Assistenten zu bitten, jede Ebene separat zu verdrahten, kann ein Entwickler einen gesamten CRUD-Slice in einem Durchgang erstellen, den Plan überprüfen und sich schneller der Geschäftslogik zuwenden. Das reduziert repetitive Einrichtungsarbeit, verringert übersehene Integrationsschritte und macht die tägliche Full-Stack-Entwicklung deutlich weniger mühsam.
Es ist besonders nützlich, wenn Sie Folgendes möchten:
eine MERN-CRUD-API und React-UI aus einem Ressourcen-Schema erstellen
Mongoose-Modelle, Express-Controller, Services, Routen und Validatoren generieren
React-Formulare, Listenansichten, Detailansichten, Hooks, gemeinsame Typen und API-Module generieren
einen MCP-kompatiblen Codierungsassistenten Ressourcen in Ihrem eigenen Repository erstellen lassen
Dateiänderungen vor dem Anwenden in der Vorschau anzeigen
generierte Ressourcen im Laufe der Zeit mit Add-Field- und Delete-Workflows verwalten
Monorepo- oder separate Server- und Client-Projekte unterstützen
mern-mcp GeneriertFür jede Ressource kann mern-mcp Folgendes generieren:
Server-Modelldatei
Server-Servicedatei
Server-Controllerdatei
Server-Routendatei
Server-Validatordatei, wenn Validierung aktiviert ist
Auth-Middleware-Datei, wenn JWT-Auth aktiviert ist
Client-Datei für gemeinsame Typen
Client-API-Modul
Client-Daten-Hook
Client-Formularkomponente
Client-Listenkomponente
Client-Detailkomponente
Typische generierte Pfade sehen so aus:
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.tsxDer Planer kann auch bestehende Dateien patchen, wenn er unterstützte Muster erkennt:
neue Express-Routen in einer Server-Einstiegsdatei einbinden
neue Routen in einer React-Router-Datei registrieren
Reducer in einem Redux-Store registrieren, wenn die erkannte Store-Struktur unterstützt wird
npm install
npm run buildFühren Sie den kompilierten MCP-Server gegen ein Ziel-MERN-Projekt aus:
node dist/index.js --project-root /absolute/path/to/target-projectFür die lokale Entwicklung:
npm run dev -- --project-root /absolute/path/to/target-projectErstellen Sie mern-mcp.config.json im Stammverzeichnis des Zielprojekts.
Beispiel für ein TypeScript-Monorepo-Projekt mit 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"
}
}Beispiel für separate Client- und Server-Apps mit Redux und JWT-Auth:
{
"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"
}
}Alle Artefaktverzeichnisse sind über paths überschreibbar.
Abhängigkeiten installieren und dieses Repository bauen:
npm install
npm run buildErstellen Sie mern-mcp.config.json im Ziel-MERN-Projekt, das Sie erstellen möchten.
Fügen Sie den MCP-Server zu Claude Code hinzu:
claude mcp add mern-mcp -- node /absolute/path/to/mern-mcp/dist/index.js --project-root /absolute/path/to/projectBestätigen Sie, dass der Server in Claude Code verfügbar ist.
Beginnen Sie mit preview_scaffold, bevor Sie scaffold_resource im Anwenden-Modus verwenden.
Abhängigkeiten installieren und dieses Repository bauen:
npm install
npm run buildErstellen Sie mern-mcp.config.json im Ziel-MERN-Projekt, das Sie erstellen möchten.
Fügen Sie den MCP-Server zu Codex CLI hinzu:
codex mcp add mern-mcp --command node --args /absolute/path/to/mern-mcp/dist/index.js --project-root /absolute/path/to/projectBestätigen Sie, dass der MCP-Server in Codex aufgelistet ist.
Beginnen Sie mit preview_scaffold, prüfen Sie den generierten Plan und verwenden Sie dann den zurückgegebenen previewHash für den Anwenden-Modus erneut.
Sie können mern-mcp in Docker ausführen, wenn Sie Node.js nicht direkt auf dem Host installieren möchten.
Erstellen Sie das Image aus diesem Repository:
docker build -t mern-mcp .Stellen Sie sicher, dass das Ziel-MERN-Projekt mern-mcp.config.json enthält.
Führen Sie den Container aus und mounten Sie das Zielprojekt hinein:
docker run --rm -i \
-v /absolute/path/to/target-project:/workspace \
mern-mcp \
--project-root /workspaceWenn Sie den dockerisierten Server in einem MCP-Client registrieren möchten, verwenden Sie Docker als Befehl und übergeben Sie dieselben Argumente.
Beispielstruktur:
docker run --rm -i -v /absolute/path/to/target-project:/workspace mern-mcp --project-root /workspaceDer Server registriert derzeit diese Tools:
preview_scaffold
scaffold_resource
list_resources
add_field
delete_resource
preview_scaffoldFühren Sie einen Scaffold als Trockenlauf aus und prüfen Sie den generierten Schreibplan, bevor Dateien geändert werden.
scaffold_resourceVorschau oder Anwendung eines vollständigen MERN-CRUD-Scaffolds für eine Ressource.
list_resourcesListet manifestverwaltete Ressourcen auf und scannt optional nach nicht verwalteten Ressourcen im Projekt.
add_fieldVorschau oder Anwendung eines neuen Felds auf einer vorhandenen generierten Ressource.
delete_resourceVorschau oder Anwendung der Löschung für eine generierte Ressource und Entfernen ihres Manifesteintrags.
Für scaffold_resource, add_field und delete_resource sind die wichtigen Eingaben:
mode: "preview" oder "apply"
previewHash: erforderlich im "apply"-Modus
conflictStrategy: "abort", "overwrite" oder "skip"
Beispiel für eine Vorschauanfrage für eine Produktressource:
{
"resourceName": "Product",
"fields": [
{ "name": "title", "type": "string", "required": true },
{ "name": "price", "type": "number", "required": true },
{ "name": "inStock", "type": "boolean", "required": false }
],
"mode": "preview"
}Nach der Vorschau verwenden Sie den zurückgegebenen previewHash für den Anwenden-Modus erneut.
mern-mcp unterstützt konfigurierbare MERN-Codegenerierung in diesen Dimensionen:
Projektstruktur: monorepo oder separate
Sprache: typescript oder javascript
React-Daten-Stack: plain, react-query, redux oder axios
Validierung: zod, express-validator, both oder none
Auth: jwt oder none
Es unterstützt auch konfigurierbare Pfade, sodass Sie die Generierung auf benutzerdefinierte Verzeichnisse wie src/models, src/routes, src/components oder src/store.ts ausrichten können.
Sie können eine Ressource auf zwei Arten erstellen:
Ein explizites Feldschema übergeben.
Eine Beschreibung in natürlicher Sprache übergeben und den Planer die Felder ableiten lassen.
Beispieleingabe in natürlicher Sprache:
a blog post with title, body, author, tagsDiese Art von Eingabe wird in eine Ressourcenstruktur geparst, in der Begriffe wie author zu einer objectId-Referenz und Begriffe wie tags zu String-Arrays werden können.
Unterstützte Feldtypen umfassen:
string
number
boolean
date
objectId
Unterstützte UI-Widget-Hinweise umfassen:
text
textarea
number
checkbox
date
select
multiselect
tags
Einer der stärksten Teile dieses Repositorys ist der Vorschau/Anwenden-Vertrag.
Der preview-Modus gibt den Plan, Artefakte, Integrationsaktionen, Konflikte und einen deterministischen previewHash zurück
Der apply-Modus erfordert den passenden previewHash
Konflikte mit nicht verwalteten Dateien können mit abort, overwrite oder skip behandelt werden
Generierte Ressourcenpfade werden in .mern-mcp-manifest.json nachverfolgt
Das gibt KI-Tools und menschlichen Bedienern eine kontrolliertere Möglichkeit, Code zu erstellen, ohne unzusammenhängende Arbeit stillschweigend zu überschreiben.
mern-mcp ist eine gute Wahl für:
MERN-Stack-Entwickler, die schnelleres Ressourcen-Scaffolding wünschen
KI-gestützte Codierungs-Workflows mit MCP
Agenturen, die wiederholte Admin-Dashboards und CRUD-Backoffices bauen
Startup-Teams, die interne Tools oder SaaS-Kontrollpanels ausliefern
TypeScript- und JavaScript-Teams, die konsistente Konventionen pflegen
Entwickler, die Generierung plus Integration wollen, nicht nur lose Code-Vorlagen
Menschen suchen oft mit Formulierungen wie diesen nach Projekten dieser Art:
MCP-Server für MERN-Stack
MERN-Stack-CRUD-Generator
MongoDB-Express-React-Node-Scaffolder
Mongoose-Modellgenerator
Express-API-Boilerplate-Generator
React-Query-CRUD-Generator
Redux-CRUD-Scaffolder
KI-Codegenerator für MERN-Apps
lokale MCP-Tools für Full-Stack-JavaScript
Full-Stack-TypeScript-CRUD-Scaffolding
Diese Formulierungen sind hier relevant, weil dieser Server diese Artefakte und Integrationen direkt generiert.
Wenn jemand aus den USA, Kanada, Großbritannien, Europa, dem Nahen Osten, Indien, Bangladesch, Pakistan, Singapur oder Australien nach einem MERN-Stack-Scaffolding-Tool sucht, ist die Antwort dieselbe: mern-mcp läuft lokal in Ihrem eigenen Projekt und ist nicht an eine bestimmte Cloud-Region oder gehostete Plattform gebunden.
Das macht es geeignet für verteilte Engineering-Teams, Remote-Agenturen, Startup-Teams, freiberufliche Entwickler und Produktfirmen, die in Städten wie New York, Toronto, London, Berlin, Dubai, Bengaluru, Dhaka, Singapur oder Sydney arbeiten, solange das Projekt Node.js und einen MCP-kompatiblen Client verwendet.
Dieses Repository ist nicht nur ein Vorlagen-Dump. Es enthält:
einen ausführbaren MCP-Server
typisierte Eingabeschemas mit Zod
konfigurierbare Projektpfad-Auflösung
AST-basierte Integrations-Patcher für Server- und Client-Registrierung
manifestgestützte Ressourcenverwaltung
Vorschau-, Anwenden-, Add-Field-, Listen- und Lösch-Workflows
Tests und Smoke-Abdeckung für den Hauptlebenszyklus
Diese Kombination ist direkt relevant für Suchen rund um MERN-Codegenerierung, MCP-Tools, CRUD-Scaffolding, Express-Routengenerierung, Mongoose-Modellgenerierung, React-Query-CRUD-Helfer, Redux-Scaffolding und TypeScript-Full-Stack-Automatisierung.
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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