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PopNx MCPServidores MCP para quienes usan IA · explicados con palabras sencillas

Cachly Dev MCP

de cachly-devversión 0.10.231i★ –iSe ejecuta en tu computadora
Nombre en el registroio.github.cachly-dev/mcp-server

Instalar

Resumen

Descripción del creador (original en inglés)

Solve it once. From then on, your AI knows. Experience for coding agents, hosted in the EU.

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": {
    "cachly-dev": {
      "command": "npx",
      "args": [
        "-y",
        "@cachly-dev/mcp-server"
      ]
    }
  }
}

Ejecuta esto en tu terminal

claude mcp add cachly-dev -- npx -y @cachly-dev/mcp-server

Abrir en Cursor

O copia la configuración tú

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

{
  "mcpServers": {
    "cachly-dev": {
      "command": "npx",
      "args": [
        "-y",
        "@cachly-dev/mcp-server"
      ]
    }
  }
}

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": {
    "cachly-dev": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@cachly-dev/mcp-server"
      ]
    }
  }
}

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 cachly-dev, 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 32403 servidores de esta categoría
  • Publicado en el registro más recientemente que el 98% de los otros 32403 servidores de esta categoría
  • Revisiones básicas iguales o mejores que el 100% de los otros 32403 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 Cachly Dev MCP?

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 (0.10.231) 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, LickityClick

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

LickityClick

de lickity.click

Create, edit and track LickityClick short links, campaigns and click stats from your AI assistant.

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.

cachly — experience for coding agents (MCP server)

Solve it once. From then on, your AI knows.

Every fix, every decision and every dead end becomes experience your AI uses at

the right moment. You build faster, and your team builds on what you figured out.

@cachly-dev/mcp-server connects cachly to Claude Code, Cursor, GitHub Copilot, Windsurf, Cline, Continue.dev, Zed, Codex CLI and Gemini CLI over MCP. It offers 124 MCP tools. Your editor lists 27 entries by default and reaches the rest through one of them, cachly_tool (details under MCP Tools below). Your AI stores a lesson after a fix, and finds it again when the same problem returns. Your Brain (the store of your lessons) lives on EU servers.

Start without an account

Claude Code
/plugin marketplace add cachly-dev/cachly-mcp

/plugin install cachly-brain@cachly

There is no JSON to write, no path to set and no key to copy. Without a key, cachly creates a test Brain on EU servers when the session starts (the plugin hook does it; the first tool call does it if the hook did not). The test Brain has 14 days of the Solo tier. After that it runs on the free tier with the same key.

Check it with claude mcp list. You should see plugin:cachly-brain:cachly … ✔ Connected. claude plugin details shows MCP servers (0) even when the server runs, because it does not count them.

The plugin adds three Claude Code hooks:

HookWhat it does
SessionStartGives your AI a short briefing: the 5 most-reused lessons (on a new Brain: starter tips)
UserPromptSubmitPuts the lessons that match your prompt next to it
StopSaves a lesson when the AI's last message clearly reports a fix. It skips messages that say something failed or is unclear. It tells you nothing when it saves.

Turn on auto-update once: /plugin → Marketplaces → cachly → Enable auto-update. Claude Code leaves it off for marketplaces outside Anthropic's own. The MCP server updates itself on every start, but the hooks come with the plugin and update only with it. If an update is waiting, the first session_start of a session says so in one line.

Keep your test Brain
npx @cachly-dev/mcp-server@latest claim

You sign in once in the browser. The test Brain then moves into your account with all its lessons. Every test key is revoked, and you get a new key that is stored where your editor and hooks look for it. The Brain restarts once, which takes about 20 seconds. If you already have a free Brain, the one-Brain limit of the free tier applies and the move is refused with a message.

Cursor, Windsurf, VS Code, Cline, Continue.dev, Zed
npx @cachly-dev/mcp-server@latest autopilot

autopilot finds the editors you use and writes the MCP config for each. It also writes the rule file each editor reads in every chat (CLAUDE.md, AGENTS.md, .cursor/rules/cachly.mdc, .github/copilot-instructions.md, .windsurfrules, .clinerules; GEMINI.md, .junie/guidelines.md and .continue/rules/cachly.md where you use Gemini CLI, Junie or Continue), which tells your AI to check its memory before a task. It adds a git hook that learns from your commits and fills your Brain from your git history. You sign in once in the browser (a device code, no password, no credit card), so the Brain belongs to your own account from the start. Restart your editor afterwards.

You can also add the server by hand (see Manual Setup). Without a key, the first tool call creates the same test Brain as in Claude Code. Without a rule file, Claude Code still starts each task with smart_recall, because the server's instructions ask for it. Gemini CLI also passes them on. Some editors do not (Cline, Continue and Zed, for example); there, the rule file from autopilot is what makes your AI use its memory.

Already inside Claude, Cursor or Copilot? Paste this to your AI:

`

Set up cachly for this project. Run: npx @cachly-dev/mcp-server@latest autopilot

Follow the browser sign-in, then restart the editor.

`

VS Code extension

Install [cachly Brain](https://marketplace.visualstudio.com/items?itemName=cachly-dev.cachly-brain). It creates your Brain on first start, with no account form.

JetBrains plugin

Install [Cachly Brain](https://plugins.jetbrains.com/plugin/32059-cachly-brain) from the JetBrains Marketplace (IntelliJ IDEA, PyCharm, GoLand, WebStorm, Rider). The status bar, the Brain health and the lessons view live in the IDE. The source is at cachly-dev/cachly-intellij. The JetBrains plugin guide shows how Claude Code, Junie and JetBrains AI Assistant get the Brain over MCP.

MCP Registry

The server is listed in the official [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers?search=cachly) as io.github.cachly-dev/mcp-server. Clients that browse the registry find it by name. The entry points at this npm package.

Guides

GuideWhat you find there
Claude Code hooks: which event to use whenSessionStart, UserPromptSubmit, PreToolUse, Stop and more, sorted by when they fire. What each one can block, add and change.
A UserPromptSubmit hook for Claude CodeThe stdin JSON, additionalContext, a working Node script and five traps to avoid.
The same hooks in VS Code and Copilot CLI, Codex CLI and Gemini CLIWhich event takes context in each editor, and the exact file setup writes there.
Comparisons: Supermemory, Zep, claude-mem, Basic Memory, mem0, LettaSide by side, each row with its source and a visible date, including when the other product fits better.
EU-hosted MCP server: what leaves your machineWhere data lands: storage in Germany, embeddings in the EU, the network edge, and a checklist.
Lessons learned for coding agentsHow to write a lesson your agent finds again: symptom, decisive fact first, what failed, files, a check. With examples and a LESSONS.md.
JetBrains plugin guideWhat the plugin does, and how Claude Code, Junie and JetBrains AI Assistant use the Brain.
Repo X-rayEnter a public GitHub repo. In a few seconds you see how many problems its team has solved, and which ones more than once.

How it works

  1. A fix, a decision or a dead end is stored as a lesson: topic, what worked, what failed, severity, file paths, commands and author.
  2. At the start of a session, your AI receives a briefing with the last session, open failures and recent lessons.
  3. When you ask for something, smart_recall looks up the lessons that match. It combines keyword search (BM25), meaning-based search and the causal graph, in 11 languages.
  4. When an error appears, causal_trace walks from the symptom to the cause and to the fix that worked.
  5. Before a deploy, brain_predict lists failure patterns from past incidents.
  6. A git hook and the CI templates add lessons from commits and from red-to-green runs.
  7. Lessons are shared in the team. Each one carries the name of whoever learned it.

To see what your AI would know before you install anything, run npx @cachly-dev/mcp-server@latest demo in a project folder. It reads your git history and prints your fixes, patterns and decisions. Nothing leaves your machine.

Our agreement with you. You can leave and take your data: npx @cachly-dev/mcp-server@latest export writes every lesson to lessons.md (to read) and lessons.jsonl (to reuse). Code excerpts are stored only if you call index_project yourself, and only on your own EU instance. Read what leaves your machine before you decide.

MCP Tools (124 total, 27 listed by default)

Your editor sees 27 entries by default: the daily tools (26 of them) and one dispatcher, cachly_tool. This is on purpose. The full list of 124 costs about 28,000 tokens in every request. The 27 listed entries cost about 8,000. All other tools (98 of them) run through the dispatcher:

cachly_tool(tool: "team_roster")                  run any of them by name

cachly_tool(tool: "team_roster", describe: true) get its schema first

Nothing is unreachable. The server dispatches by name, so team_roster called directly still works. Set CACHLY_ALLE_WERKZEUGE=1 to list all 124. Set CACHLY_PROFILE=lean to list 8 plus cachly_tool, or CACHLY_PROFILE=recall to list the 3 read-only tools.

Session and lessons (most used)
ToolWhat it does
`session_start`Full briefing: last session, open failures, recent lessons, Brain health
`session_end`Save what you built; extract lessons from the summary and the git log
`learn_from_attempts`Store a structured lesson after any fix, deploy or discovery (with author, visibility)
`recall_best_solution`The known fix for a topic, with its success and failure history
`smart_recall`Hybrid BM25 + semantic + causal-graph search, 11 languages, quality-reranked
`remember_context`Keep architecture findings, decisions and file summaries
`compact_recover`Recover your context after you hit the context-window limit
Team Brain and org knowledge graph
ToolWhat it does
team_learn / team_recallShare lessons across the team with author attribution
team_confirmA reviewer confirms a lesson (senior or peer); confirmed lessons rank higher in recall
team_assign_role / team_roster / team_whoamiRoles (admin, reviewer, contributor, viewer), enforced once an admin is set
team_auditAdmin-only governance trail: every role change and lesson confirmation
`brain_who_knows`Find your team's experts on a topic, ranked from authorship
`brain_file_map`Experts and lessons per file, before you touch it
`team_expertise_map`The team's skills matrix in one table
`brain_collab_pairs`Who works with whom, with bus-factor alerts
`brain_portability`Config snippets for 7 MCP clients, so the same Brain serves any model
`skill_gaps`Knowledge blind spots: unresolved failures, missing attribution
`brain_coverage`A 0–100 health score for the knowledge of your codebase
madc_deliberateSpecialist AI agents vote to resolve contradictory lessons
memory_crystalizeDistill all lessons into a Crystal for instant team context
team_crystallizeA Team Crystal: fixes that 2 or more teammates reached independently
Causal intelligence
ToolWhat it does
`causal_trace`Root-cause analysis through the causal knowledge graph
`brain_predict` / brain_predict_failuresPredict likely failures before they happen

| `brain_from_git` | Fill people, file

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

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