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Projectmem

de riponcmversión 0.3.5i★ –iSe ejecuta en tu computadora
Nombre en el registroio.github.riponcm/projectmem

Instalar

Resumen

Descripción del creador (original en inglés)

Coding agent memory — one local MCP server for every project. Warns before repeating failed fixes.

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: Búsqueda y memoria de IA

Instalación

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

Antes de instalar

Necesitas

  • PyPIuv de Python instalado (para el comando uvx)

¿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": {
    "projectmem": {
      "command": "uvx",
      "args": [
        "projectmem"
      ]
    }
  }
}

Ejecuta esto en tu terminal

claude mcp add projectmem -- uvx projectmem

Abrir en Cursor

O copia la configuración tú

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

{
  "mcpServers": {
    "projectmem": {
      "command": "uvx",
      "args": [
        "projectmem"
      ]
    }
  }
}

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": {
    "projectmem": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "projectmem"
      ]
    }
  }
}

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 riponcm, 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 Búsqueda y memoria de IAi

  • Más estrellas que el 0% de los otros 7226 servidores de esta categoría
  • Publicado en el registro más recientemente que el 85% de los otros 7226 servidores de esta categoría
  • Revisiones básicas iguales o mejores que el 100% de los otros 7226 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 Projectmem?

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 (0.3.5) llegó al registro hace 6 días.

¿Qué apps pueden usarlo?

Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) en tu computadora.

¿Qué puedo usar en su lugar?

En la misma categoría: Context7, Codebase Memory, Exa

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

Context7

de upstash

Up-to-date docs for AI agents

Computadora o nube★ 64.224MITActualizado hace 3 días
Instalar

Codebase Memory

de DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Se ejecuta en tu computadora★ 48.148MITActualizado hace 20 días
Instalar

Exa

de exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Se ejecuta en la nube★ 5213MITActualizado hace 44 días
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.

🎉 v0.3.5 is out — precheck recognises a file however its path is spelled, and the summary stays small even when entries are long. See what changed →

We don't make AI smarter. We make it experienced. Coding agent memory — the local-first memory + judgment layer for AI coding agents. One MCP server for every project. Stop re-reading your project every session. Stop repeating yesterday's bug.

Website • Guide • Demo • Changelog • Paper

https://github.com/user-attachments/assets/e055988e-7253-4ba9-92fc-95d3d4bcd763

pjm visualize — every case your project solved, what failed on the way, and what it saved. Generated locally from .projectmem/events.jsonl .


## 🚀 Start here — five minutes, once

*Five minutes if you follow along here. Want to be shown instead — every

command, the exact output it prints back, and the dashboards at the end?

Take [the complete setup guide](https://projectmem.dev/blog/projectmem-complete-guide-ai-coding-agent-memory).*

New to projectmem, or upgrading from 0.1.x / 0.2.x? Since 0.3.0 one MCP

server serves every project, so this is the last time you configure anything.

1. Install or update

`bash

pip install -U projectmem

`

2. Find the projects you already have

`bash

pjm doctor

`

It looks where code lives — ~/Developer, ~/code, ~/projects, your cloud

folders, and every drive on Windows — and lists projects with memory that

aren't registered yet. Anything it missed, add by hand:

`bash

pjm project register "/Users/you/Developer/repos/ossdrop"

`

3. Register them

`bash

pjm doctor --fix

`

4. Point your AI at all of them with one config

`json

"mcpServers": {

"projectmem": {

"command": "/absolute/path/to/python",

"args": ["-m", "projectmem.mcp_server"]

}

}

`

No --root, no cwd — that's what makes it serve everything. Per-client

instructions (Claude Desktop, Claude Code, Cursor, Antigravity, Codex) are in

MCP Integration; pjm init prints this block

with your own Python path filled in. Then fully restart the client — MCP

servers only load on a cold start.

5. Check your work

`bash

pjm doctor

`

Add --online if you also want it to tell you when a newer projectmem is out

— projectmem makes no network calls otherwise, and --auto turns that into a

once-a-day check if you prefer.

Run it again after editing the config. It flags any client still pinned to a

single repo — the most common reason a new project is invisible to your agent.

All green? You're done. From here on it is one command per repo:

`bash

pjm init

`

Your agent reads what the project already learned instead of rediscovering it,

and writes down what it finds. Fewer tokens, no repeated dead ends, memory that

outlives the session.


What is coding agent memory?

Coding agent memory is a persistent record of what happened while building a project — the issues hit, the approaches attempted, the fixes that worked and the decisions made — stored so an AI coding agent can read it at the start of a new session. Without it every session begins from zero.

projectmem is an open-source agent memory layer built for that job. It is local-first: memory lives in a plain .projectmem/ directory inside your repository, with no cloud, no account and no telemetry — the only network call it can make is an update check you turn on yourself. A native MCP server exposes 17 tools to Claude Code, Claude Desktop, Cursor, Antigravity and Codex, so your agent reads memory and logs its work on its own.

Unlike chat-history memory tools, projectmem stores typed events — issues, attempts, fixes, decisions, notes — which is what makes its signature feature possible: a pre-commit warning that fires *before* you repeat an approach that already failed in this project.

pip install projectmem

cd your-project && pjm init


🎬 Watch the demo

Full screen-recorded tutorial- watch on YouTube

📚 Docs

DocWhat's in it
[Complete setup guide](https://projectmem.dev/blog/projectmem-complete-guide-ai-coding-agent-memory)The full walkthrough on the web — install, MCP setup per client, pjm doctor, your first logged issue, and both dashboards. Every terminal output is captured from a real run.
[TUTORIAL.md](https://github.com/riponcm/projectmem/blob/main/TUTORIAL.md)15-minute step-by-step walkthrough — set up projectmem on your own project, watch the lifecycle, see the pre-commit warning fire.
[CHANGELOG.md](https://github.com/riponcm/projectmem/blob/main/CHANGELOG.md)Release history. Latest: v0.3.5 — precheck matches every spelling of a path, and long entries no longer bloat the summary.
[Research paper (arXiv:2606.12329)](https://arxiv.org/abs/2606.12329)*PROJECTMEM: A Local-First, Event-Sourced Memory and Judgment Layer for AI Coding Agents* — the peer-readable version: design, Memory-as-Governance framing, capability comparison, and the 207-event dogfooding study.
[LICENSE](https://github.com/riponcm/projectmem/blob/main/LICENSE)MIT

The Problem

Every new AI session starts from zero. Claude, Cursor, Aider — they all forget yesterday's decisions, repeat failed debugging attempts, and burn millions of tokens reconstructing context from raw source files.

The model isn't the problem. The architecture is. Stateless models need a memory cortex.

The Solution

projectmem is the local-first memory + judgment layer that sits above your AI tools. It captures every failed attempt, decision, and gotcha — then injects that experience back into future AI sessions. Git tracks *what* changed. projectmem tracks *why* it changed, what was tried, and what failed.

Install

First time here? → [The complete setup guide](https://projectmem.dev/blog/projectmem-complete-guide-ai-coding-agent-memory)

walks the whole path end to end: install, connecting Claude Desktop, Claude Code,

Cursor, Codex or Antigravity, checking it with pjm doctor, and reading your

memory back through the dashboards — with the real terminal output at every step.

Three commands to a project that remembers:

pip install projectmem

cd your-project pjm init

That's it. pjm init installs three git hooks (pre-commit warnings, post-commit classification, post-merge tracking), auto-starts a real-time file watcher, inherits cross-project memory if available, and creates .projectmem/. Capture is active from minute one.

The canonical command is projectmem. A pjm alias is installed for speed.


✨ New in 0.3.5 — warnings for every spelling, and a summary that stays small

Precheck recognises a file however its path is spelled. Events store project-relative paths, so asking about ./src/auth.py, an absolute path, a path through a symlinked folder or a Windows C:\ path matched nothing, and precheck called a file with known failures "Safe to modify". Every spelling now gets the same warnings, and checking is faster on large logs. get_issue("1") and get_issue("#1") find issue 0001. (#26)

Long entries no longer bloat the summary. 0.3.4 capped how many entries the summary shows, not how long each one is. Records are now clipped at 300 characters, and a fixed issue takes one line. On a real 238-event project the summary went from 8,974 tokens to 3,458. (#29, #30)

Upgrading? Run `pjm init` once in each project. The instructions now ask agents for shorter records, and pjm init refreshes AI_INSTRUCTIONS.md, keeping your previous copy as AI_INSTRUCTIONS.md.bak.

The #26 fixes were contributed by @vishalhabib99, and #29 was reported and fixed by @bigfree.

✨ New in 0.3.4 — memory that stays small, and warnings you can trust

The summary no longer grows forever. Notes were capped, but Recent issues and Decisions listed everything ever logged, so on an aged project reading the memory cost more than reading the code. Every open issue is still shown — the newest 20 in full, older ones by id — while fixed issues are capped at the newest 10 and decisions at the newest 15, each with a line saying what was left out and where to find it. On a test project with 25 issues and 60 decisions the summary went from about 2,900 tokens to about 1,100. (#19)

Commits are filed under the code they change. Auto-capture used the first changed path in git's sort order, which was usually the regenerated .projectmem/summary.md — so valid memories were flagged stale and the real file lost its history. The location is now the source file the commit is about, with deletions, renames, merges and a repository's first commit handled. (#20)

Stale warnings no longer depend on your time zone. A 0.3.3 speed-up compared git's local-time commit dates with UTC event times as text: west of UTC, recent stale memories were never flagged; east of UTC, fresh ones were flagged at once. Both sides are compared in UTC now, and events already filed under .projectmem/ stop warning without your log being rewritten.

*

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

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