Prototipo · Versión preliminar: todos los servidores del registro oficial, sincronizados cada 30 minutos. Las reseñas y las cuentas llegarán en una etapa posterior.
PopNx MCPServidores MCP para quienes usan IA · explicados con palabras sencillas

LayerMap

de coffeecoprojectversión 0.1.35i★ –iSe ejecuta en tu computadora
Nombre en el registroio.github.coffeecoproject/layermap

Instalar

Resumen

Descripción del creador (original en inglés)

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

Los tres pilares de PopNx MCP

Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.

Qué puedes hacer con él

Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.

  • Conexión: Se ejecuta en tu computadora
  • Transporte: stdio
  • Categoría: Otros

Instalación

Elige la app de IA que usas y copia la configuración.

Antes de instalar

Necesitas

  • npmNode.js instalado (para el comando npx)

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

Ejecuta esto en tu terminal

claude mcp add layermap -- npx -y layermap mcp

Abrir en Cursor

O copia la configuración tú

Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json

{
  "mcpServers": {
    "layermap": {
      "command": "npx",
      "args": [
        "-y",
        "layermap",
        "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.

Abrir en VS Code

O copia la configuración tú

Pégalo en .vscode/mcp.json de tu proyecto

{
  "servers": {
    "layermap": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "layermap",
        "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.

Qué puede hacer

Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.

Revisiones básicasi

Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 6 nov 2026

  • ✓ Superada

    El creador coincide con el repo

    El nombre en el registro se verificó con la cuenta de GitHub coffeecoproject, dueña del repo

  • … Aún sin revisar

    Sigue en mantenimiento

    Todavía no hemos leído este repo en GitHub

  • … Aún sin revisar

    Tiene licencia

    Todavía no hemos leído este repo en GitHub

  • – No aplica

    El endpoint responde

    Este se ejecuta en tu computadora; no hay endpoint en internet

  • – No aplica

    Inicio de sesión con OAuth

    Se ejecuta en tu computadora y usa ajustes locales en su lugar

  • … Aún sin revisar

    Sin instrucciones ocultas en las descripciones de herramientas

    Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet

Comparado con otros en Otrosi

  • Más estrellas que el 0% de los otros 32417 servidores de esta categoría
  • Publicado en el registro más recientemente que el 96% de los otros 32417 servidores de esta categoría
  • Revisiones básicas iguales o mejores que el 100% de los otros 32417 servidores de esta categoría

Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.

Preguntas frecuentes

¿Es seguro LayerMap?

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.

¿Qué claves o códigos necesita?

El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.

¿Se ejecuta en mi computadora o en la nube?

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).

¿Sigue en mantenimiento?

El repo de GitHub cambió por última vez –, y la última versión (0.1.35) llegó al registro ayer.

¿Qué apps pueden usarlo?

Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.

¿Qué puedo usar en su lugar?

En la misma categoría: Spec Driven Development, Remote Desktop Commander, FOGA node

Alternativas

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

Spec Driven Development

de formulahendry

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

Se ejecuta en tu computadora★ 440MITActualizado hace 14 meses
Instalar

Remote Desktop Commander

de desktop-commander

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

Se ejecuta en la nube★ 211Actualizado ayer
Instalar

FOGA node

de garyyang-finchip

A Finch OG Agent cell as an MCP server: read the world, dry-run and take ERC-8414 tenders by policy.

Computadora o nubeActualizado hoy
Instalar

README del creador

Abrir el README

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.

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

Solo se muestra el principio; lee el resto en el repo

Pregunta a PopNx