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Dreamd

de botzrDevversión 1.2.2i★ –iSe ejecuta en tu computadora
Nombre en el registroio.github.botzrDev/dreamd

Instalar

Resumen

Descripción del creador (original en inglés)

Auditable agent memory: lessons cite their sources, and bad memories can be traced and removed.

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

  • 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": {
    "dreamd": {
      "command": "npx",
      "args": [
        "-y",
        "dreamd-mcp"
      ]
    }
  }
}

Ejecuta esto en tu terminal

claude mcp add dreamd -- npx -y dreamd-mcp

Abrir en Cursor

O copia la configuración tú

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

{
  "mcpServers": {
    "dreamd": {
      "command": "npx",
      "args": [
        "-y",
        "dreamd-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": {
    "dreamd": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "dreamd-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 botzrDev, 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 7236 servidores de esta categoría
  • Publicado en el registro más recientemente que el 95% de los otros 7236 servidores de esta categoría
  • Revisiones básicas iguales o mejores que el 100% de los otros 7236 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 Dreamd?

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 (1.2.2) llegó al registro anteayer.

¿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: 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.

dreamd

Agent memory you can audit. When a memory goes bad, trace it to its source, see what it fed, and remove it.

dreamd is local-first, long-term memory for AI agents. Every memory is a line in a file in your repo, every lesson your agents learn cites the events it came from, and each dream cycle commits its lessons to git. When an agent acts on something wrong, you can find the memory that caused it, see which lessons it fed, and take it out, with a receipt.

npx -y dreamd-mcp setup   # scaffold .agent/ and wire your harness

npx -y dreamd-mcp # MCP server (stdio): what the harness spawns

Recorded live on dreamd 1.2.0, sped up 1.5x: blame finds the event behind a bad answer, forget removes it with a receipt, and the same query comes back without it. Tape: docs/assets/blame-forget.tape.

Works today with Claude Code, Cursor, Cline and other MCP-aware harnesses. Self-hosted, single binary, Apache-2.0 core.

If you want agent memory you can trace and undo, star the repo to follow releases. When a memory goes wrong, an issue with the blame output helps us fix it.


Why auditable memory

Memory is the layer of an agent stack you usually can't see into. A prompt can be read and a model can be swapped, but when memory goes wrong there is rarely a way to tell what the agent believed, where that belief came from, or what else it touched.

That matters more now that memory is an attack surface. The OWASP Top 10 for Agentic Applications lists memory and context poisoning (ASI06): an attacker, a bad tool result or a plain mistake plants a "fact" that the agent keeps acting on in later sessions. The defenses OWASP points to start with knowing the source of every memory and being able to remove one cleanly (OWASP agentic top 10).

dreamd is built for that response:

You need todreamd gives you
See what drove an answerdreamd blame lists the stored memories behind a recall, with ids, timestamps, source and score. dreamd recall --explain prints the salience factors for each hit
Know where a lesson came fromEvery lesson in LESSONS.md cites the episodic events it was promoted from, and the provenance ledger records which event fed which lesson and index entry
Check the record is consistentdreamd doctor --provenance recomputes the ledger's Merkle root and lists orphan, missing and corrupt edges. Read-only
Remove a bad memorydreamd forget removes the event and the lesson state that names it. --dry-run shows what would change; --proof writes a forget-receipt/1.0 file
Review what agents learned.agent/ is committed with your code, and each dream cycle commits its output as dreamd: cycle YYYY-MM-DD. Review new lessons with git diff or in a pull request, and undo a cycle with git revert
Read everything yourselfPlain JSONL and Markdown. cat, grep and git log work on every byte

What dreamd does not do. It does not detect or block poisoned writes, and it does not filter injected lesson content (SECURITY.md). source_harness is asserted by the caller, not verified. The provenance ledger and the forget receipt are unsigned, and there are no trust labels yet. dreamd makes bad memory traceable and removable; it does not make it impossible. See Roadmap for what comes next.


The audit loop in four commands

Say an agent keeps repeating advice you know is wrong.

# 1. Find the memories behind it

npx -y dreamd-mcp blame "deploy without tests" --explain

2. Check the lesson it came from and what that lesson cites

cat .agent/semantic/LESSONS.md npx -y dreamd-mcp doctor --provenance

3. Preview, then remove the bad event (stop the daemon, npx -y dreamd-mcp watch, first; forget refuses while it runs)

npx -y dreamd-mcp forget evt_... --dry-run npx -y dreamd-mcp forget evt_... --proof forget-receipt.json

4. Review the change like code

git diff .agent/

After a forget, doctor --provenance reports the removed event's old ledger edges as orphans and exits 1. That is expected: the ledger is append-only, so it keeps the record that the event once existed.

To undo a whole dream cycle instead, git revert its dreamd: cycle commit with the daemon stopped, then run npx -y dreamd-mcp doctor --repair to rebuild the recall index.


Install

npm (recommended)
npx -y dreamd-mcp setup   # scaffold .agent/ and write the harness MCP config

npx -y dreamd-mcp # MCP server (stdio): your harness spawns this

stdio is the default transport. dreamd mcp --bind 127.0.0.1: is an opt-in Streamable HTTP server at /mcp. It is unauthenticated, and it is only in source builds with --features mcp-http. See docs/mcp-transports.md.

dreamd needs a project root sentinel (.git/, Cargo.toml, package.json or pyproject.toml).

setup prompts when it has a TTY. In scripts and non-interactive shells, pass --yes --harness claude|cursor|both (--harness none or --no-write-mcp scaffolds without touching any MCP config).

Cargo / from source
git clone https://github.com/botzrDev/dreamd.git

cd dreamd cargo install --path crates/dreamd-cli

See CONTRIBUTING.md for the full dev setup.


Quick start (under a minute)

If ~/your-project is a brand-new folder, run git init first.

cd ~/your-project

npx -y dreamd-mcp setup

Optional: shared daemon, recommended when several agents write

npx -y dreamd-mcp watch

Reload your harness. setup already wired the dreamd MCP server, so the harness spawns npx -y dreamd-mcp itself.

Ask the agent to search memory for something it learned earlier. It calls search_nodes and recalls prior context, with the source harness on every hit.

cat .agent/episodic/AGENT_LEARNINGS.jsonl

npx -y dreamd-mcp dream --dry # preview the lesson the next cycle would write npx -y dreamd-mcp doctor

The npm shim does not put dreamd on PATH. Use npx -y dreamd-mcp on the npm path, or cargo install --path crates/dreamd-cli for the dreamd binary. From 1.2.1 the shim forwards every dreamd command; the 1.2.0 shim did not forward recall, score, status, archive and migrate.

Adapters: Claude Code · Cursor · Cline

Recorded live, sped up 1.5x: Claude Code writes the lesson, OpenCode reads it back through the same .agent/ folder. Tape: docs/assets/demo.tape.


How agents learn

Agents write episodes (what happened, how painful it was, how important) through MCP append_node. The dream cycle clusters episodes by skill_action and promotes a recurring pattern into a lesson in LESSONS.md. With an API key it composes the lesson with an LLM under a $0.10 per-cycle spend cap; without one it writes a deterministic lesson and makes no network call. Either way the lesson cites the events it came from, and every output is staged and committed through one redo WAL, so a crash leaves the store as it was or rolls the cycle forward.

Recall ranks episodes and lessons with BM25 × salience (age decay, pain, importance, recurrence). Recall is deliberately lexical; vector recall is not shipped (docs/vectors.md). Formula: docs/salience.md.


What dreamd writes

LocationContentsCommit?
/.agent/Episodic JSONL, semantic lessons, personal prefsYes (this is the shared memory)
/.agent/.dreamd/Local index, daemon state, config template, provenance ledgerNo (gitignored by init)
~/.agent/registry.tomlWhich projects have a storeNo
~/.agent/dreamd.sockDaemon API socket (while running)No

setup scaffolds the store by calling init, then writes the harness MCP config. Both are idempotent. To uninstall from a machine, run npx -y dreamd-mcp uninstall. On a tty it waits for y; pass --yes in a script. Without a tty and without --yes it exits 2 and changes nothing. Project .agent/ stores are left in place. npx -y is npx's flag, not dreamd's --yes. npx -y dreamd-mcp init --uninstall-project drops only the registry entry; dreamd init puts it back and does not rewrite the store.


All inspection commands

The MCP surface is two tools (search_nodes, append_node). Everything else is CLI over the same files. dreamd --help is the reference for flags.

CommandWhat it does
dreamd recall Ranked search as a markdown table. --explain prints the salience factors per hit; --without / --without-cluster drop hits before top-k, so you can see the answer without a suspect memory
dreamd blame Which stored memories drove a query's ranking: id, timestamp, skill_action, bm25, salience, total, layer. --json for one compact array
dreamd scoreTop memories by salience alone, no query
dreamd salience-driftSalience distribution, top clusters, and drift against the snapshot from seven days earlier. See docs/observability.md
dreamd dream --dryPrint the LESSONS.md the next cycle would write, without writing
dreamd forget Remove one episodic event and the lesson state that names it. --dry-run writes nothing; --proof writes a forget-receipt/1.0 file (a receipt, not a signed proof). Refuses while the daemon is running
dreamd doctor --provenanceRecompute the provenance ledger's Merkle root and list orphan edges, missing edges and corrupt lines. Read-only. See docs/provenance.md
`dreamd memory branch\checkout\branches\delete\diff\bisect`Deprecated in 1.2.0, removed in 2.0. .agent/ is plain files, so use git. See docs/branching-guide.md

Architecture (one paragraph)

Agents talk to dreamd over MCP. On Linux and macOS the MCP server proxies to a single-writer daemon (dreamd watch) over HTTP on a Unix domain socket, or runs in-process when no daemon is present. On Windows it proxies to loopback dreamd watch and exits 2 when that daemon is down. One writer lock covers every process that writes a project. The coordinator appends to AGENT_LEARNINGS.jsonl and feeds a Tantivy BM25 index; recall ranks hits with the salience formula, and each hit carries source_harness and skill_action. Details: ARCHITECTURE.md · SPEC.md · docs/http-api.md. Warm recall latency (local Criterion benches) is in PERF.md.


Roadmap

Direction, not dated commitments. Full view: ROADMAP.md.

  • Trust labels. A label on every memory saying where it came from and how far to trust it, joined along provenance edges, so a lesson from an untrusted source can't drive a privileged action. Needs its own spe

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

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