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)
Cited structure of Java/Spring/Angular codebases: dependencies, tables, endpoints, hotspots.
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。
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": {
"stratigraph": {
"command": "npx",
"args": [
"-y",
"stratigraph",
"mcp"
]
}
}
}在终端中运行这条命令
claude mcp add stratigraph -- npx -y stratigraph mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"stratigraph": {
"command": "npx",
"args": [
"-y",
"stratigraph",
"mcp"
]
}
}
}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": {
"stratigraph": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"stratigraph",
"mcp"
]
}
}
}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。
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 GitHub 账户 imashishsharma 验证,该账户拥有此仓库
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(2.2.1)于6天前进入注册中心。
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, Detailing Manager
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.
Connect your auto detailing studio's tasks, cars, clients and revenue to Claude or ChatGPT.
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。
Upgrade Spring Boot with your tests as the judge, and map large Java, Spring and Angular codebases with every claim cited.
Website: https://imashishsharma.github.io/stratigraph/ · open source, runs locally
npx stratigraph upgrade plan --to 3.5 # read-only: what will break, with file:line citations
npx stratigraph upgrade run --to 3.5 --ai claude-code
OpenRewrite's recipe does most of an upgrade. The upgrade agent handles what it leaves broken, on Maven and Gradle builds alike.
upgrade-report.md with the evidence and the options.| Benchmark (details) | OpenRewrite alone | stratigraph |
|---|---|---|
| 10 public Spring Boot apps: every previously passing test still passes, no human edits | 0 / 10 | 5 / 10 (+2 stopped at a real decision) |
| 9 apps it had never seen (details) | — | 8 / 9 |
| Gradle: realworld-example-app, JHipster 7.9 (details) | — | 68/68 parity; JHipster stopped at 1 error (needs JHipster 8) |
| Time and AI cost per app | — | 1–14 min, $0–2.54 |
Tried it? Tell us what you upgraded, and what it got wrong, in Discussions. Upgrading a fleet of Boot 2.x services? Become a design partner and run it on real code with the maintainer.
npx stratigraph scan . # extract, mine git history, analyse, write the report: one command
stratigraph mcp): 13 read-only tools such as what_breaks_if, who_knows and where_is_table_written, for Claude Code, Cursor or any MCP client.Measured on 20 public repositories against hand-labelled ground truth: entity and table recall 100%, endpoint recall 99%, DI edges resolved 95% (scorecard).
Stratigraphy is how archaeologists read a site: layer by layer, deducing the order things happened from what sits on top of what. stratigraph does the same to a large codebase — it reads the source, reads the git history, and reconstructs how the thing came to be shaped the way it is.
Aimed at monoliths and multi-module builds of 100k+ LOC where nobody remembers why things are the way they are. Java, Kotlin and Angular first. It runs on repositories that do not compile, have never had node_modules installed, and use layouts nobody has used since Ant — because those are exactly the repositories nobody remembers.
npm install -g stratigraph # or run every command through: npx stratigraph
cd ~/work # the fact store lands here, not in the repo stratigraph init --repo ../some-monolith # create the fact store stratigraph extract --repo ../some-monolith # parse the source into facts stratigraph history --repo ../some-monolith # mine git: churn, coupling, authors stratigraph analyze --repo ../some-monolith --no-llm # cycles, clusters, hotspots stratigraph report --repo ../some-monolith --out ./arch open ./arch/index.html
TypeScript and Angular analysis works out of the box — the extractor ships in this package and runs on the Node you already have. Java and Kotlin need a JDK 17+ and one more command, stratigraph fetch-extractor, which downloads the extractor jar and verifies it against a checksum pinned in this package. No API key is needed for any of the above: --no-llm is the whole structural report, and a model only ever adds prose on top of it.
stratigraph doctor # says which of these your machine can do right now
Static analysis produces facts. The LLM produces interpretation. The LLM never invents a fact.
Every node and edge comes from a parser, from git log, or from a build file. Every claim in a generated report carries a provenance reference — a file and line, a commit sha, or a fact-table row. When the model wants to assert something it cannot cite, the correct output is "no evidence found".
This is enforced in the schema, not only in prompts: interpretation lives in different tables from facts, edges are marked fact or inferred, and a citation row has a CHECK constraint forcing it to point at something real. See ADR-0002.
The whole pipeline runs with --no-llm and still produces a useful report.
Quality is measured, not asserted (ADR-0035). stratigraph bench runs the whole pipeline over 20 public repositories, each pinned to a commit in bench/corpus.yaml, and scores the output against ground truth labelled without the tool — from each repository's source, build files, migrations and git log — in bench/truth/. Every number below is from bench/scorecard.md, which lists every miss by name.
| Metric | Target | 2.0 |
|---|---|---|
| Non-source files (lockfiles, manifests, tests, generated) in the hotspot top 20 | 0 | 0 |
| Hotspot top-10 overlap with a senior engineer's labelled list | ≥ 60% | 66% (92/138) |
| JPA entity recall, with the physical table name | ≥ 90% | 100% (146/146) |
| Table recall | ≥ 90% | 100% (274/274) |
| HTTP endpoint recall | ≥ 95% | 99% (519/520) |
| Injection edges resolved | ≥ 85% | 95% (215/226) |
| Deployables found as containers / containers that are deployables | 100% | 100% (67/67) / 100% (67/67) |
| File roles matching the labels | ≥ 95% | 96% (535/557) |
| Views rendered without a coverage statement | 0 | 0 |
| Repositories the pipeline completed on | 20/20 | 20/20 |
The corpus spans Spring Boot monoliths and microservices (petclinic and its Kotlin, REST, legacy-XML and Angular variants, JHipster in Maven, Gradle and OAuth2 flavours, eladmin, piggymetrics, killbill, initializr, OpenMRS, nacos, Spring Cloud Gateway, Spring Boot Admin), Apache Dubbo at 4,000 Java files, and two large TypeScript workspaces (bitwarden/clients at 6,400 files, analog). The labels are only as good as their labelling: where a miss turned out to be a label contradicting the source at the pinned commit, the label was corrected and the evidence recorded in the truth file.
Run it yourself:
stratigraph bench --fetch # clones the corpus into ~/.cache/stratigraph/corpus
stratigraph bench --private ../your-repo # aggregates only, nothing that names a file
npm install -g stratigraph
Requires Node 18.18 or newer. Nothing else, until you analyse Java — the Java extractor needs a JDK 17+ available, and tells you so rather than crashing. stratigraph doctor is the honest inventory of what your machine can do:
$ stratigraph doctor
ok stratigraph v1.4.0, fact-store schema v1 ok node v20.11.1 on darwin-arm64 ok git git version 2.50.1 warn java 1.8.0_432 from JAVA_HOME is below JDK 17; the Java extractor will not run (this limits the analyser, not the code it can analyse) warn jvm extractor jar not found — see the README for the two commands that build it ok ts extractor dist/extractors/typescript/main.js (built, no JDK required)
只显示了开头部分;其余内容请在仓库中阅读