Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
Cited structure of Java/Spring/Angular codebases: dependencies, tables, endpoints, hotspots.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"stratigraph": {
"command": "npx",
"args": [
"-y",
"stratigraph",
"mcp"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add stratigraph -- npx -y stratigraph mcpPégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"stratigraph": {
"command": "npx",
"args": [
"-y",
"stratigraph",
"mcp"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"stratigraph": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"stratigraph",
"mcp"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub imashishsharma, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (2.2.1) llegó al registro hace 6 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.
En la misma categoría: Spec Driven Development, Remote Desktop Commander, Python MCP
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
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.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
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)
Solo se muestra el principio; lee el resto en el repo