Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Beschreibung vom Entwickler (englisches Original)
Call graph for coding agents: callers up to HTTP routes, callees, usages for TS/JS, Go, Python, Java
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"layermap": {
"command": "npx",
"args": [
"-y",
"layermap",
"mcp"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add layermap -- npx -y layermap mcpIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"layermap": {
"command": "npx",
"args": [
"-y",
"layermap",
"mcp"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"layermap": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"layermap",
"mcp"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 6. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto coffeecoproject bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.1.35) kam gestern in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Node.js auf deinem Computer.
In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, Dechonet MCP
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
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Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
English · 中文
LayerMap tells your coding agent what calls a function and what changing it affects, up to the HTTP routes, in one call. With at most 15 requests, Claude Code on Opus 5.5 found 99.9% of affected endpoints with LayerMap vs 76.0% without; with no limit, it found about the same and cost 48% less, or 27% less without the task that gained most (benchmark).
Resolved by each language's compiler or type checker, not guessed from names by tree-sitter: calls through interfaces, base classes, templates and decorators link as the compiler links them, for TypeScript, JavaScript, Go, Python and Java.
A real Claude Code session on Miniflux , replayed: one map call finds every endpoint, then the agent confirms them in source.
A layered map of your codebase for coding agents. LayerMap gives Claude Code, Codex, CodeBuddy Code, Pi, DeepSeek Harness and other MCP clients read-only tools that answer, in one call, what an agent otherwise works out with dozens of searches:
It maps TypeScript, JavaScript, Go, Python and Java with each language's own compiler, so calls through interfaces, base classes, templates and decorators resolve as the compiler resolves them, including the ones text search misses. In WeChat mini-programs, it also links each page's and component's template (.wxml) to the methods it binds and the components it shows, and each event a component emits to the handlers the pages bind to it, so callers reach the pages.
In Miniflux, one call on Storage.MarkFeedAsRead finds all four ways a request reaches it, each with its route:
DECLARATION internal/storage/entry.go: Storage.MarkFeedAsRead m656-680 exported
← called by internal/api/feed.go: handler.markFeedAsRead m140-155 @149 ← called by internal/fever/handler.go: handler.handleWriteFeeds m492-519 @508 ← called by internal/googlereader/handler.go: handler.markAllAsReadHandler m1261-1338 @1311 ← called by internal/ui/feed_mark_as_read.go: handler.markFeedAsRead m14-30 @24 [1] internal/api/feed.go: handler.markFeedAsRead m140-155 ← used as value by internal/api/api.go: Serve f25-84 @61 "PUT /v1/feeds/{feedID}/mark-all-as-read" [1] internal/googlereader/handler.go: handler.markAllAsReadHandler m1261-1338 ← used as value by internal/googlereader/handler.go: Serve f44-64 @62 "POST /reader/api/0/mark-all-as-read" [1] internal/ui/feed_mark_as_read.go: handler.markFeedAsRead m14-30 ← used as value by internal/ui/ui.go: Serve f18-180 @77 "POST /feed/{feedID}/mark-all-as-read" … (the Fever API, then on down to main.go: main)
m and f mark methods and functions with their lines; @ is the line of the call, and the quoted route is what it is registered under: the HTTP method and the full path, with the /v1 prefix its subrouter adds. In Java, Python and TypeScript the route shows on the handler itself, as in @GetMapping("/{id}") route "GET /api/tasks/{id}".
Impact questions ("which HTTP endpoints does changing this affect?") on public Go, Python and Java projects, graded blind against truth sets cross-checked with each language's own toolchain:
| With LayerMap | Without | |
|---|---|---|
| Endpoints found, at most 15 requests (Claude Code on Opus 5.5, 6 tasks × 3 runs) | 99.9% | 76.0% |
| Cost / time at that limit (Opus 5.5) | +12% / +4% | |
| Endpoints found, no request limit (Opus 5.5, 6 tasks × 2 runs) | 100% | 99.7% |
| Cost / time, no request limit (Opus 5.5, maps built ahead) | −48% / −33%; −27% / −21% without the task that gained most | |
| Ripple tasks: runs leaving other features' tests passing (Opus 5.5, 4 tasks × 3 runs) | 12 of 12 | 12 of 12 |
Endpoints found, at most 15 requests (gpt-5.5, 6 tasks × 3 runs) | 97.9% | 58.8% |
| Used unprompted by Claude Code / Codex (plugin installed, two rounds) | 12 of 12 / 12 of 12 | — |
| Endpoints found, no request limit (Claude Code / Codex, 0.1.5) | 100% / 100% | 99.0% / 100% |
| Claude Code cost, no request limit (0.1.5 re-run; first round −32%) | −33% | |
| Codex input tokens, no request limit (current defaults) | +14% | |
Time, no request limit (Claude Code on claude-opus-5 / Codex, 0.1.5) | +25% / +20% | |
| Failing tests the change check lists (Go / Python, functions made to fail) | 100% / 94–98% | — |
| Ripple tasks: runs leaving other features' tests passing (Codex / Claude Code, 4 tasks × 6 runs with, × 3 without) | 23 of 24 / 11 of 24 | 3 of 12 / 4 of 12 |
| Everyday tasks, no impact analysis needed: done right / time (Claude Code and Codex, 8 tasks × 2 runs) | 32 of 32 / +12–31% | 32 of 32 |
With a tight budget, the map finds far more of the affected code, at 12–24% more cost or tokens. With no limit, both agents find nearly everything either way. Claude Code costs a third to a half less with the map. On Opus 5.5 it was also a third faster, though one task accounts for much of that gap and the maps were built ahead; on claude-opus-5 it was a quarter slower. Codex's current defaults already search lean, so the map no longer saves it tokens; at reasoning effort max, in the first round, it saved 55%. Codex with the map explores more widely, which takes longer. On requests whose obvious change breaks another feature, the change check helped Codex keep to the requested feature. Claude Code saw which tests of other features it had changed but often kept the broader change on purpose, so it showed no clear difference; on Opus 5.5 it broke nothing with or without the map, and the check cost 17% more. On small local tasks the map changed nothing but cost about a fifth more time and money. These are small samples on tasks written by LayerMap's authors. The report has the setup, the published tasks and the limitations.
Other tools give agents part of this. LayerMap combines compiler accuracy with whole-chain traces in one local map:
| Tree-sitter code graphs (codegraph, GitNexus, …) | Language servers and IDEs (Claude Code's LSP tool, Serena, JetBrains) | Embedding search (Claude Context, Augment) | LayerMap | |
|---|---|---|---|---|
| How calls are linked | Matched by names, imports and framework rules, often with confidence scores | The compiler's own resolution | Not linked; similar code is retrieved | Resolved by each language's compiler or type checker |
| Callers traced to routes and handlers | In several tools, at varying depth | One level per request (JetBrains: 5 by default) | — | Up to 8 levels in one call |
| Kept as a map | Yes, with file watching | No, answered live by a running server | An index of code chunks | Yes, brought up to date on every call |
| Runs on your machine | Yes; some send anonymous telemetry | Yes | Usually with cloud embeddings | Yes, and sends nothing |
Another tool fits better if you need:
Claude Code
/plugin marketplace add coffeecoproject/layermap
/plugin install layermap@layermap
Codex
codex plugin marketplace add coffeecoproject/layermap
codex plugin add layermap@layermap
CodeBuddy Code
codebuddy plugin marketplace add coffeecoproject/layermap
codebuddy plugin install layermap@layermap
Pi
pi install npm:layermap
DeepSeek Harness
npx layermap setup dsh
This adds LayerMap to every dsh profile. Each session maps the project dsh was started in, and npx layermap remove dsh undoes it.
In every agent, start a new session in a Git repository and ask as usual. LayerMap tells the agent when the map helps. A session started in a folder holding several repositories, or one that moves to another repository, works too: each map tool call maps the repository its path names. The first time a session starts a version of LayerMap, npm installs that pinned layermap package into LayerMap's cache; later sessions start it from there, even offline.
Claude Code asks once before each map tool runs in a project. Choose "don't ask again", or run npx layermap allow claude to allow the plugin's read-only tools everywhere.
After an edit. When the agent changes code, project_check_changes lists what the change affects: the routes, jobs and commands that reach the changed functions, what the map cannot see, and the existing tests related to the change. When the changed code serves several areas (packages or modules), it names each one with its tests, and it names the existing tests the diff rewrote, so a change meant for one feature does not quietly change the others. Environment variables and configuration keys are linked by name only, which no compiler sees, so when the diff removes one from a file, the check names the files that still read or set the old name. In the same way, when the change reaches a route's handler or renames a route, it names the code and templates that request that path: a frontend's fetch, a generated API client, a redirect or a link. When the change adds an import between two modules of the project overview, it names it, and says when the two now depend on each other; whether that direction suits the project's layers is for the agent to judge. When a declaration the change adds reads almost the same as code the project already has, it names both, so the agent can use the existing code instead of a copy. When the change takes away the last call to a declaration, as when new code replaces old, it names that declaration, so the agent can delete what the change left behind. The map does not link a field or type to the code reading it, so for one the change touches, the check searches for its references and follows that code up to the entry points and tests, as possibly affected. It never writes or runs tests. In Claude Code and CodeBuddy Code the plugin asks the agent once, before it finishes, to run this check for each repository it edited code in and has not checked since, whether through its edit tools or shell commands, which count for the code files they name (changes another session makes in the same work tree do not count); the Pi extension does the same after the agent's own edits. Set LAYERMAP_STOP_CHECK=0 to turn that off. Codex and Deep
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