Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
Code generation from JSON recipes, linked type graphs, and API schemas across 11 languages.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
METAENGINE_API_URL你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"metaengine": {
"command": "npx",
"args": [
"-y",
"@metaengine/mcp-server"
],
"env": {
"METAENGINE_API_URL": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add metaengine --env METAENGINE_API_URL=your-value -- npx -y @metaengine/mcp-server运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"metaengine": {
"command": "npx",
"args": [
"-y",
"@metaengine/mcp-server"
],
"env": {
"METAENGINE_API_URL": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"metaengine": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@metaengine/mcp-server"
],
"env": {
"METAENGINE_API_URL": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
METAENGINE_API_URL env这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过域名 metaengine.eu 验证(注册中心会核实域名所有权)
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(1.5.0)于2个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。
同一分类中有:Spec Driven Development, Remote Desktop Commander, Python MCP
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Local-only Python MCP server for the Files.com API.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
Generate related source files from a type graph, a compact JSON recipe, or an API schema through your MCP client.
MetaEngine combines structured classes, interfaces, enums, collections, and generics with target-language code supplied in customCode. Explicit references connect that code to the same type graph, so the generator can resolve names and imports across the batch. Use it for models, services, adapters, or other structures you describe; the format does not prescribe an application architecture.
Node.js 18 or later is required. Add the server to your MCP client's configuration:
{
"mcpServers": { "metaengine": { "command": "npx", "args": ["-y", "@metaengine/mcp-server@1.5.0"] } } }
For Claude Code:
claude mcp add metaengine -- npx -y @metaengine/mcp-server@1.5.0
The hosted service requires no API key or account. MCP clients include Claude Code, Claude Desktop, Cursor, Cline, and others with stdio support.
Call generate_from_recipe with these arguments:
{
"recipe": { "recipeVersion": 1, "language": "typescript", "typeScriptOptions": { "relativeImportExtension": "js" }, "classes": [ { "name": "Customer", "id": "customer", "properties": { "id": "string", "name": "string" } }, { "name": "Order", "properties": { "customer": { "ref": "customer" }, "total": "number", "note?": "string" } } ] }, "outputPath": "src/models" }
The local MCP server expands the recipe into the existing generation payload, sends that payload to the MetaEngine API, and writes the returned files. Add named templates and parameter rows when structures repeat. Existing customCode, templateRefs, imports, decorators, inheritance, and generic definitions remain available.
A version-controlled recipe can be invoked with {"recipeFilePath":"specs/models.recipe.json"}. Reading a file avoids resending its contents in the tool call. Files still need to be authored or maintained.
Recipe grammar and examples · Generation guide · Language examples
| Tool | Purpose |
|---|---|
generate_from_recipe | Expand compact JSON fields, named templates, and local JSON input rows into the existing type graph, then generate files. |
generate_code | Generate from the complete native JSON type graph, including arbitrary target-language code with explicit references. |
load_spec_from_file | Read a native generate_code payload from a local JSON file. |
generate_openapi | Generate a typed client from an OpenAPI document supplied inline or by URL. |
generate_graphql | Generate a typed client from GraphQL SDL, with optional named fragments. |
generate_protobuf | Generate a typed client from Protocol Buffers definitions. |
generate_sql | Generate model types from SQL DDL. |
metaengine_initialize | Load generation rules and language notes for the assistant. |
Type and model generation supports TypeScript, Python, Go, C#, Java, Kotlin, Groovy, Scala, Swift, PHP, and Rust. Client generation targets Angular, React, TypeScript Fetch, Go net/http, Java Spring, Python httpx, C# HttpClient, Kotlin Ktor, Rust Reqwest, and Swift URLSession.
generate_code, load_spec_from_file, and generate_from_recipe share generation and file-writing behavior:
outputPath chooses the local output directory; the default is the MCP server's working directory.skipExisting defaults to true. Set it to false to overwrite generated files.dryRun: true returns generated file contents without writing them. Generation still calls the hosted API.For Node16/NodeNext TypeScript ESM, use typeScriptOptions: {"relativeImportExtension":"js"}. Other TypeScript output retains extensionless relative imports by default.
Field maps remove repeated property metadata. Templates describe repeated structure once and bind explicit parameter values. Local JSON inputs can supply those values from a file you already maintain. The adapter executes no JavaScript from a recipe.
Savings depend on the amount of repetition, the chosen model and tokenizer, and the surrounding agent workflow. Custom business logic still needs to be written. A recorded development fixture compares a 59-interface recipe with its expanded payload; it measures JSON bytes, not model tokens or usage-limit guarantees.
The compact format keeps one readable path for common declarations and the existing native fields for advanced code. Native type expressions and customCode remain specific to their target language. Review and compile generated code in your project, including its dependencies and compiler settings.
The local MCP server runs over stdio and performs recipe expansion, declared local file reads, and generated-file writes. The hosted MetaEngine API performs ephemeral processing of the expanded generation payload and returns source files.
The server does not automatically scan or upload existing project source files. Source or customCode content explicitly included in a generation request is part of that request and is sent to the hosted MetaEngine API. Values read from recipe inputs are included only when the recipe uses them in the expanded payload.
Submitted generation content and generated file contents are not persisted or logged; anonymous operational metadata is retained. See the Privacy Policy and Terms for the processing and retention details.
A single MCP call can produce many files, reducing required tool operations. Model responses are a separate measure: in the recorded TypeScript runs Opus often issued one Write per response, while Sonnet usually batched the Writes. The corrected benchmark findings separate those counts and retain output-token totals and pass rates.
For reproducible measurements across languages, models, and spec shapes, see benchmark/ — a self-contained harness with the prompts, judging tools, and 15 canonical result folders. Numbers there are illustrations from one author's runs at N=5 per cell; reproduce in your own environment to see what holds for you.
MIT
This repository contains public documentation, examples, benchmarks, and issue tracking for MetaEngine MCP Server. The compiled npm package is available at @metaengine/mcp-server. The server implementation is maintained in a private repository.