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Builderforce Memory

de SeanHoggversión 2026.10.42i★ –iSe ejecuta en tu computadora
Nombre en el registroio.github.SeanHogg/builderforce-memory

Instalar

Resumen

Descripción del creador (original en inglés)

Token-saving persistent memory for AI agents: recall durable facts instead of re-reading files.

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
  • Debes completar: BUILDERFORCE_API_KEY

Instalación

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

Antes de instalar

  • Revisiones básicas: 1 de 1 superadas
  • Se ejecuta en tu computadora con los permisos de tu usuario (archivos, red, apps).
  • Debes completar tú: BUILDERFORCE_MEMORY_FILE, BUILDERFORCE_MEMORY_READONLY, BUILDERFORCE_API_KEY

Los valores marcados como secretos son llaves de tu cuenta. Nunca los compartas ni los pegues en un chat.

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": {
    "builderforce-memory": {
      "command": "npx",
      "args": [
        "-y",
        "@seanhogg/builderforce-memory-mcp"
      ],
      "env": {
        "BUILDERFORCE_MEMORY_FILE": "your-value",
        "BUILDERFORCE_MEMORY_READONLY": "your-value",
        "BUILDERFORCE_API_KEY": "your-value"
      }
    }
  }
}

Ejecuta esto en tu terminal

claude mcp add builderforce-memory --env BUILDERFORCE_MEMORY_FILE=your-value --env BUILDERFORCE_MEMORY_READONLY=your-value --env BUILDERFORCE_API_KEY=your-value -- npx -y @seanhogg/builderforce-memory-mcp

Completa los valores vacíos antes de ejecutarlo.

Abrir en Cursor

O copia la configuración tú

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

{
  "mcpServers": {
    "builderforce-memory": {
      "command": "npx",
      "args": [
        "-y",
        "@seanhogg/builderforce-memory-mcp"
      ],
      "env": {
        "BUILDERFORCE_MEMORY_FILE": "your-value",
        "BUILDERFORCE_MEMORY_READONLY": "your-value",
        "BUILDERFORCE_API_KEY": "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.

Abrir en VS Code

O copia la configuración tú

Pégalo en .vscode/mcp.json de tu proyecto

{
  "servers": {
    "builderforce-memory": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@seanhogg/builderforce-memory-mcp"
      ],
      "env": {
        "BUILDERFORCE_MEMORY_FILE": "your-value",
        "BUILDERFORCE_MEMORY_READONLY": "your-value",
        "BUILDERFORCE_API_KEY": "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.

Valores que debes completar

  • BUILDERFORCE_MEMORY_FILE env
    Absolute path to the JSON snapshot that makes memory survive restarts. Defaults to ~/.builderforce-memory/memory.json, which every MCP host on the machine shares.
  • BUILDERFORCE_MEMORY_READONLY env
    Set to 1 to expose recall only (disables memory_remember and memory_forget).
  • BUILDERFORCE_API_KEY secreto env
    Builderforce tenant API key (bfk_*). When set, additionally exposes the token_usage and model_efficiency cost tools.

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 SeanHogg, 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 7241 servidores de esta categoría
  • Publicado en el registro más recientemente que el 100% de los otros 7241 servidores de esta categoría
  • Revisiones básicas iguales o mejores que el 100% de los otros 7241 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 Builderforce Memory?

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?

Debes completar: BUILDERFORCE_API_KEY

¿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 (2026.10.42) llegó al registro hoy.

¿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.

@seanhogg/builderforce-memory-mcp

Expose @seanhogg/builderforce-memory to any MCP client. One token-saving tool core over a pluggable MemoryBackend, three transports:

TransportFactoryConsumed asUse when
In-process (Claude Agent SDK)createMemoryMcpServer(backend)the returned type:"sdk" objectthe consuming product is TS and runs @anthropic-ai/claude-agent-sdk in-process — lowest latency
stdiorunStdio(backend) / npx @seanhogg/builderforce-memory-mcp{ type:"stdio", command, args }any language / separate process; decouples the SSM+IndexedDB deps from the consumer
HTTP (Streamable)createMemoryHttpHandler(backend, { authToken }){ type:"http", url, headers }multi-tenant / networked (builderforce.ai hosting, remote agents)

Technical report & peer review. This transport is reviewed in the Evermind technical report's adversarial PEER-REVIEW.md. Note before exposing the HTTP handler publicly: the authToken check is a non-constant-time string compare (timing channel) and the handler shares one `backend` with no per-tenant isolation — a single token reads every tenant's facts. Despite the "multi-tenant" note above, real isolation (token→namespace mapping, constant-time compare, rate limiting) is not yet implemented. Tracked as EVM-3 in the Builderforce.ai Consolidated Gap Register. Resolved in v2026.6.34: the HTTP handler now uses a constant-time token compare and per-tenant namespace isolation (see the resolution addendum in PEER-REVIEW.md).

Why this saves tokens

The point of an external memory store is fetch-on-demand instead of pinning your whole memory file into every prompt. That only pays off if recall is *selective*, so the caps are enforced server-side in tools.ts:

  • memory_recall returns a ranked top-K (default 5, hard-capped), never the store.
  • Each entry's content is truncated (default 500 chars) before it hits context.
  • There is no "return everything" tool — a dump-all is more expensive than inlining.
  • memory_compact shrinks a fact the local Evermind has already ABSORBED down to a one-line pointer stub, so it stops filling context. It is lossless: a recall probe must pass first, and the original is archived (recall still returns it) — see below. It writes through the live store, which keeps memory and the on-disk snapshot in agreement.
  • Recall ranks by hybrid fusion (BM25 ⊕ optional CPU SSM embedding, RRF, MMR) and then weights by importance (×(0.5+importance)) and a 90-day half-life recency decay — createLocalMemoryStoreBackend({ ranking: false }) turns the signals off.

Tool descriptions are prescriptive ("call this *before* answering when…") because recent Claude models reach for tools more conservatively; the trigger condition in the description is what drives should-call rate. Pair this with prompt caching (keep the tool set identical across tenants so the cached prefix survives) and context editing (prune stale recalled facts) for the full win.

The seam

Everything is written against MemoryBackend:

interface MemoryBackend {

recall(query: string, topK: number): Promise ; // semantic get(key: string): Promise ; // exact recallByTag(tag: string, limit: number): Promise ; remember?(input: RememberInput): Promise ; // optional → read-only backends omit forget?(key: string): Promise ; }

Ship the local MemoryStoreBackend (IndexedDB via @seanhogg/builderforce-memory) today; drop in a networked builderforce.ai adapter later with zero changes to tools or transports.

Quick start — in-process with the Claude Agent SDK

import { query } from "@anthropic-ai/claude-agent-sdk";

import { createMemoryMcpServer, createLocalMemoryStoreBackend } from "@seanhogg/builderforce-memory-mcp";

const backend = await createLocalMemoryStoreBackend(); // IndexedDB (fake-indexeddb in Node) const memory = await createMemoryMcpServer(backend); // type:"sdk" config

for await (const msg of query({ prompt: "What language does this user prefer? Check memory first.", options: { mcpServers: { builderforce_memory: memory }, allowedTools: ["mcp__builderforce_memory__*"], // auto-approve, no prompts }, })) { if (msg.type === "result" && msg.subtype === "success") console.log(msg.result); }

The snapshot is shared — the server watches it

With persistFile set, the store lives in memory and the JSON snapshot is the source of truth across process lifetimes. Other processes edit that file too (the BuilderForce VS Code extension rewrites absorbed entries to stubs in place), so before every operation the backend stats the file and re-hydrates from disk when it changed underneath — otherwise this server, still holding the pre-edit bodies, would re-snapshot over that work on its next write. Its own writes are stamped (mtime + size + content hash) the moment they land, so the steady-state cost is one stat and there is no write-loop.

SSM-embedding recall — including on a headless host (no GPU)

With no model configured the local backend ranks recall lexically (BM25). Point it at an Evermind checkpoint and the ordering becomes the SSM embedding's cosine ranking fused with the lexical one (Reciprocal Rank Fusion — dense ⊕ sparse, so exact tokens like identifiers and error codes are still caught). Every memory_recall result names the ranker it used, so a degrade to lexical is never silent:

Ranked by: semantic recall (SSM embedding fused with lexical).

Ranked by: lexical recall (fallback - no embedding model loaded).

The stdio/HTTP servers do not need a GPU for this. EvermindLM is a pure-CPU model and EvermindLM.embed() mean-pools + L2-normalises the same hidden state the GPU HybridMambaModel.embed() does, to the same contract. Configure it with:

EnvMeaning
BUILDERFORCE_MEMORY_MODELPath to a .evermind package holding an evermind-lm.
BUILDERFORCE_MEMORY_TOKENIZERTokenizer JSON for that checkpoint. Default .tokenizer.json.
BUILDERFORCE_MEMORY_VECTORSVector-cache path. Defaults beside the memory snapshot.

Vectors are cached across process lifetimes (stamped with the model's fingerprint, so an adapted checkpoint invalidates them), because a per-session subprocess that re-embedded the whole store on its first recall would cost more than the lexical ranking it replaces.

In-process hosts pass an embedder directly — reuse an already-loaded GPU Evermind runtime rather than standing up a second model:

const backend = await createLocalMemoryStoreBackend({ runtime: ssmMemoryService.runtime });

Either way, recall quality improves automatically as that model is adapted/distilled.

Experience — what Evermind has done (opt-in)

Facts are one kind of learned item; experience is another. An *episode* is a recorded demonstration (a program and the UI steps a person took in it), a *skill* is what Train Once compiles from one (typed values become parameters, secrets never stored, irreversible clicks gated for approval), and a *run* is one execution with its audit trail. The domain lives in @seanhogg/builderforce-memory-engine; this server keeps it durable and exposes it.

Set BUILDERFORCE_MEMORY_EXPERIENCE=1 to register the tools (Synapse does). Off by default, so ordinary coding-agent installs never carry them in their tool list.

Tools
experience_infoSnapshot file, screenshot folder, model path, counts.
experience_forget_allDelete every episode, screenshot, skill and run (confirm: true). Memories and the model are untouched.
episode_save / _list / _get / _forgetDemonstrations. Screenshots go in episodes/ / and are deleted with the episode.
skill_preview / _compile / _list / _get / _forget / _schedule, skills_dueTrain Once and routines.
run_start / _step / _finish / _list / _getRuns and their audit trail (newest 500 kept).
experience_trainAdapt the private model (BUILDERFORCE_MEMORY_MODEL) on every procedure it has not learned, through the engine's one adaptation recipe. The previous model is kept as .prev. Opt-in curate: true first leaves out procedures whose runs mostly fail and near-copies (of each other, or of the 200 most recently learned), listing each one dropped; it is reconsidered next time.

Stored beside the memory snapshot as experience.json (shared across processes exactly like memory.json) plus episodes/. Never served to a token-selected tenant of the HTTP handler.

One-shot install into any MCP host (not just Claude)

# Auto-detect installed agents and register the memory server into each:

npx -y -p @seanhogg/builderforce-memory-mcp builderforce-memory-install

npx -y -p @seanhogg/builderforce-memory-mcp builderforce-memory-install --host=all npx -y -p @seanhogg/builderforce-memory-mcp builderforce-memory-install --host=cursor,windsurf

Writes the stdio server entry into each host's own config, idempotently and with .bak backups. Supported hosts: Claude Code, Claude Desktop, Cursor, Windsurf, VS Code, Cline, Gemini CLI, Codex CLI. Every agent points at one shared store (resolveMemoryFile(): ~/.builderforce-memory/memory.json, or the legacy ~/.claude/builderforce-memory/memory.json when that is where the live store is; override with --memory-file / BUILDERFORCE_MEMORY_FILE; the hook script resolves the same way), so a fact remembered in one agent is recalled in another. --readonly drops the write tools; --local= runs a checkout for development.

The same launch spec is exported for programmatic use: buildServerSpec() / installMemoryServer() (see src/install/).

Claude Code: the self-driving "memory combo"

Registering the server gives Claude Code the memory *tools*. For Claude Code the installer ALSO wires hooks so memory is self-driving instead of advisory (skip with --no-hooks):

HookBehaviour
SessionStartInject a digest of the top durable memories.
PreCompactFlush durable learnings before the window is summarised.
UserPromptSubmitContextual recall — score memories against the prompt and inject the relevant ones, so a stored fact is retrieved at the *decision point*, not only at session start.
StopAutonomous capture — if the user's last message was a durable instruction/correction and it wasn't consolidated this turn, BLOCK the stop with a directive to memory_remember. Capture flows through the MCP write path (never racing the snapshot); a stop_hook_active guard means at most one nudge per turn.

All four point at one generated, dependency-free hook script (~/.claude/builderforce-memory/bfmem-hook.mjs, four modes) plus a companion skill. Idempotent + .bak-safe. Source of truth: src/install/claude-hooks.ts (installClaudeCombo / bfmemHookSource).

Quick start — stdio (any process / language)

npx -y @seanhogg/builderforce-memory-mcp        # serves the local MemoryStore over stdio
mcpServers: {

builderforce_memory: { type: "stdio", command: "npx", args: ["-y", "@seanhogg/builderforce-memory-mcp"] }, }

Env: BUILDERFORCE_MEMORY_DB (db name), BUILDERFORCE_MEMORY_READONLY=1 (drop write tools).

Quick start — HTTP (multi-tenant)

BUILDERFORCE_MEMORY_TOKEN=secret PORT=8787 npx @seanhogg/builderforce-memory-mcp-http
mcpServers: {

builderforce_memory: { type: "http", url: "http://localhost:8787", headers: { Authorization: "Bearer secret" }, }, }

Or moun

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

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