프로토타입 · 미리 보기: 공식 레지스트리의 모든 서버를 담고 있으며 30분마다 동기화해요. 리뷰와 계정 기능은 다음 단계에서 열려요.
PopNx MCPAI를 쓰는 사람을 위한 MCP 서버 · 쉬운 말로 설명해요

LayerMap

제작자: coffeecoproject버전 0.1.35i★ –i내 컴퓨터에서 실행
레지스트리 이름io.github.coffeecoproject/layermap

설치

개요

제작자가 쓴 설명(영어 원문)

Call graph for coding agents: callers up to HTTP routes, callees, usages for TS/JS, Go, Python, Java

PopNx MCP의 세 기둥

이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.

할 수 있는 일

이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.

  • 연결 방식: 내 컴퓨터에서 실행
  • 전송 방식: stdio
  • 카테고리: 기타

설치

쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.

설치하기 전에

  • 기본 점검: 1개 중 1개 통과
  • 내 컴퓨터에서 내 사용자 계정의 권한(파일, 네트워크, 앱)으로 실행돼요.
  • 레지스트리에 입력해야 할 키가 나와 있지 않아요.

필요한 것

  • npmNode.js 설치(npx 명령어용)

어떤 앱을 쓰세요?

위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.

Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요

{
  "mcpServers": {
    "layermap": {
      "command": "npx",
      "args": [
        "-y",
        "layermap",
        "mcp"
      ]
    }
  }
}

터미널에서 이 명령어를 실행하세요

claude mcp add layermap -- npx -y layermap mcp

Cursor에서 열기

또는 설정을 직접 복사하기

프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요

{
  "mcpServers": {
    "layermap": {
      "command": "npx",
      "args": [
        "-y",
        "layermap",
        "mcp"
      ]
    }
  }
}

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

VS Code에서 열기

또는 설정을 직접 복사하기

프로젝트의 .vscode/mcp.json에 붙여 넣으세요

{
  "servers": {
    "layermap": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "layermap",
        "mcp"
      ]
    }
  }
}

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.

선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.

이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.

할 수 있는 일

내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.

기본 점검i

누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검

  • ✓ 통과

    제작자와 저장소 일치

    레지스트리 이름이 GitHub 계정 coffeecoproject 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요

  • … 아직 점검 안 함

    계속 관리되고 있음

    아직 GitHub에서 이 저장소를 읽어 오지 않았어요

  • … 아직 점검 안 함

    라이선스 있음

    아직 GitHub에서 이 저장소를 읽어 오지 않았어요

  • – 해당 없음

    엔드포인트 응답

    내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요

  • – 해당 없음

    OAuth로 로그인

    내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요

  • … 아직 점검 안 함

    도구 설명에 숨겨진 지시 없음

    내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요

기타 카테고리의 다른 서버와 비교i

  • 이 카테고리의 다른 서버 32424개 중 0%보다 스타가 많아요
  • 이 카테고리의 다른 서버 32424개 중 96%보다 최근에 레지스트리에 공개됐어요
  • 기본 점검 결과가 이 카테고리의 다른 서버 32424개 중 100%와 같거나 더 좋아요

레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.

자주 묻는 질문

LayerMap, 안전한가요?

해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.

어떤 키나 코드가 필요한가요?

레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.

내 컴퓨터에서 실행되나요, 클라우드에서 실행되나요?

내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).

아직 관리되고 있나요?

GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.1.35)은 어제 레지스트리에 올라왔어요.

어떤 앱에서 쓸 수 있나요?

Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.

대신 쓸 수 있는 건 뭐가 있나요?

같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, BankBridge

대안

같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.

카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i

Spec Driven Development

제작자: formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

내 컴퓨터에서 실행★ 440MIT14개월 전 업데이트
설치

Remote Desktop Commander

제작자: desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

클라우드에서 실행★ 211어제 업데이트
설치

BankBridge

제작자: bankbridge-money

Works in any MCP agent, including local models. Read-only bank accounts, spending, investments.

클라우드에서 실행오늘 업데이트
설치

제작자의 README

README 열기

제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.

LayerMap

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:

  • What calls this, and what does changing it affect? Callers traced up to 8 levels, to the HTTP routes, handlers, jobs and commands they start from.
  • What does it call? Callees down to 8 levels.
  • What is here? Modules, each file's declarations, and every usage of a symbol.
  • What did my edit affect? The routes, jobs and commands the uncommitted changes reach, and the existing tests related to them.

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.

Example

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}".

Results

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 LayerMapWithout
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 1212 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 243 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.

How LayerMap differs

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 linkedMatched by names, imports and framework rules, often with confidence scoresThe compiler's own resolutionNot linked; similar code is retrievedResolved by each language's compiler or type checker
Callers traced to routes and handlersIn several tools, at varying depthOne level per request (JetBrains: 5 by default)—Up to 8 levels in one call
Kept as a mapYes, with file watchingNo, answered live by a running serverAn index of code chunksYes, brought up to date on every call
Runs on your machineYes; some send anonymous telemetryYesUsually with cloud embeddingsYes, and sends nothing

Another tool fits better if you need:

  • more languages, since tree-sitter graphs cover 30 or more;
  • renaming and refactoring, from language servers;
  • search by meaning, from embedding search;
  • search across many repositories, with Sourcegraph.

Install

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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