Context7
Up-to-date docs for AI agents
Descripción del creador (original en inglés)
Free RAM on Windows with the user's own Mem Reduct via its clean hotkey, without admin prompts.
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.
MEMREDUCT_MCP_COOLDOWNNecesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Descargar el archivo .mcpb del creador
El enlace lleva al archivo del propio creador; no lo alojamos ni lo reempaquetamos. Abre el archivo y Claude Desktop lo instalará.
Ejecuta esto en tu terminal
claude mcp add memreduct --env MEMREDUCT_MCP_COOLDOWN=your-value -- npx -y memreduct-mcpCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"memreduct": {
"command": "npx",
"args": [
"-y",
"memreduct-mcp"
],
"env": {
"MEMREDUCT_MCP_COOLDOWN": "your-value"
}
}
}
}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": {
"memreduct": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"memreduct-mcp"
],
"env": {
"MEMREDUCT_MCP_COOLDOWN": "your-value"
}
}
}
}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.
MEMREDUCT_MCP_COOLDOWN envEsta 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 RepressedAlliance, 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 (0.1.1) llegó al registro hace 4 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js, MCPB en tu computadora.
En la misma categoría: Context7, Codebase Memory, Exa
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
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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.
Let AI agents (Claude Code, Codex, Cursor, Claude Desktop…) free RAM on Windows with your own [Mem Reduct](https://github.com/henrypp/memreduct), so a model, render or build that needs memory right now can get it, without admin prompts and without dialogs to click away.
中文说明
AI agents on Windows run long jobs on their own: builds, model inference, renders, many sessions and MCP servers side by side. Memory fills up along the way, and an agent has no way to give it back: idle sessions keep their pages resident, and trimming other programs' memory needs administrator rights the agent doesn't have. Mem Reduct can do it, but only when a person clicks it.
memreduct-mcp closes that gap: the Mem Reduct you already run cleans at the moments an agent needs it, and the agent is told what happened.
Mem Reduct already runs elevated in your tray. This server presses Mem Reduct's clean memory hotkey. Windows delivers registered hotkeys to the elevated Mem Reduct even from an unelevated agent, so no UAC prompt, scheduled task or admin service is involved. The server then waits until Mem Reduct records the clean (StatisticLastReduct in its ini) and measures available RAM before and after.
A hotkey clean shows no confirmation and no modal dialog. That is why this server does not use memreduct.exe -clean: the command line always ends with a message box that someone has to click.
This project does not include Mem Reduct. Mem Reduct is GPL-3.0 software by Henry++; this server only presses its hotkey.
Agents can't feel memory pressure, and written guidance alone isn't enough: in a 14-hour video job, an agent with this server's instructions never cleaned on its own, while the PC spent 75 minutes under 1 GB available. So in Claude Code the plugin also ships hooks, which run at each agent step:
| Moment | What happens |
|---|---|
| Before heavy work (subagents, workflows, background jobs, builds, renders), under 25% available | Cleans first. Measured gains fade within minutes under load, so this is the moment that counts. |
| A tool fails with an out-of-memory error (not GPU memory) | Cleans and tells the agent a retry is reasonable. |
| Under 15% for at least 30 seconds | Tells the agent the figures and the largest processes. Once per session, again after recovery or after 15 minutes. |
| Under 6% | Cleans at the next step. |
| Low again within 5 minutes of a clean | Doesn't clean again. Tells the agent the clean didn't hold, so it should lower parallelism, wait, or tell you. |
All sessions share one lock and cooldown. Hooks only run while an agent is working, so for the hours when none is, also set Mem Reduct's own *clean when usage is above* to about 92%.
Set MEMREDUCT_MCP_NEED_PCT, MEMREDUCT_MCP_WARN_PCT, MEMREDUCT_MCP_CRITICAL_PCT or MEMREDUCT_MCP_REARM_PCT to change the thresholds, and MEMREDUCT_MCP_HOOKS=off to turn the hooks off. What the hooks did is logged to %USERPROFILE%\.memreduct-mcp\hook-log.jsonl (memory figures, tool names and session ids only).
Other clients get the tools and the server's instructions, and no hooks yet, so whether the agent cleans on its own is up to the agent.
| Tool | What it does |
|---|---|
memory_status | Total, available and committed RAM, plus the largest processes. Read-only. |
clean_memory | Triggers a Mem Reduct clean and returns available RAM before and after, freedMB, and Mem Reduct's own figure when its result log is on. Optional needed_mb skips the clean when that much is already free. Has a cooldown (default 120 s, env MEMREDUCT_MCP_COOLDOWN). |
memreduct_setup_check | Says whether Mem Reduct is installed, running and has the hotkey enabled, and what to fix if not. |
clean_memory then also returns the amount Mem Reduct itself reports (memreductReported), so you don't have to trust the server's own measurement./plugin marketplace add RepressedAlliance/memreduct-mcp
/plugin install memreduct@memreduct-mcp
The server is on npm as memreduct-mcp:
codex mcp add memreduct -- npx -y memreduct-mcp
The server itself tells Codex when to clean. For the longer version Claude Code gets, also copy skills/memreduct/SKILL.md to %USERPROFILE%\.codex\skills\memreduct\SKILL.md (optional; new Codex sessions pick it up).
In clients configured with JSON (Cursor, Windsurf, Claude Desktop and others), add:
{
"mcpServers": { "memreduct": { "command": "npx", "args": ["-y", "memreduct-mcp"] } } }
Download memreduct-mcp.mcpb from Releases and open it, or drag it onto Claude Desktop's Settings > Extensions page. The cooldown can be changed in the extension's settings.
Clone the repository; dist/index.cjs is a self-contained bundle with no npm install needed. Use command node with argument C:\path\to\memreduct-mcp\dist\index.cjs.
Only at the right moment. Cleaning trims every program's working set and drops the standby cache, so available RAM jumps. How much depends on how much idle memory programs are holding. On a 16 GB test laptop, a process holding 6 GB of idle memory brought available RAM down to 3.6 GB; one clean_memory call brought it back to 10.9 GB (Mem Reduct's log: "Cleanup (Hotkey), 7.72 GB"). Right after a previous clean, with 10 GB already free, the same call freed under 1 GB.
Idle agent sessions are where it holds up best. With 8 long-lived Claude Code sessions (40 processes with their MCP servers) left idle after some work, one clean took their working set from 2.81 GB to 0.42 GB, and five minutes later they were at 1.02 GB. Their commit charge stayed at about 4 GB: cleaning frees physical RAM, it does not end processes or lower the commit charge.
Programs read those pages back from disk when they touch them again, so cleaning does not make a PC faster in general. It helps when a memory-hungry job is about to start and won't fit. The tool's cooldown and the bundled skill steer agents toward that use and away from cleaning on a schedule.
clean_memory then reports cleaned: false with a hint.npm install
npm run build # bundles src/ into dist/index.cjs npm test # end-to-end: starts the server and really cleans memory npm run test:policy # the hooks' decisions, without touching memory npm run pack:mcpb # builds memreduct-mcp.mcpb for Claude Desktop
MIT