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Brainllm

von miisodevVersion 13.3.1i★ –iLäuft auf deinem Computer
Name in der Registryio.github.miisodev/brainllm

Installieren

Überblick

Beschreibung vom Entwickler (englisches Original)

Self-hosted memory for LLMs in TriliumNext, structured by the server and editable by you.

Die drei Säulen von PopNx MCP

Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.

Was du damit machen kannst

Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.

  • Verbindung: Läuft auf deinem Computer
  • Transport: stdio
  • Kategorie: Suche & KI-Gedächtnis
  • Das musst du eintragen: TRILIUM_BASE_URL, TRILIUM_ETAPI_TOKEN, TRILIUM_PASSWORD, BRAINLLM_OWNER_PASSWORD, BRAINLLM_OAUTH_SECRET

Installation

Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.

Bevor du installierst

  • Basischecks: 1 von 1 bestanden
  • Läuft auf deinem Computer mit den Rechten deines Benutzerkontos (Dateien, Netzwerk, Apps).
  • Das trägst du selbst ein: TRILIUM_BASE_URL, TRILIUM_ETAPI_TOKEN, TRILIUM_PASSWORD, BRAINLLM_MODE, BRAINLLM_TZ, BRAINLLM_OWNER_PASSWORD, BRAINLLM_OAUTH_SECRET, BRAINLLM_PUBLIC_URL, BRAINLLM_ALLOW_UNAUTHENTICATED_HTTP, BRAINLLM_TRUST_PROXY

Als geheim markierte Werte sind Schlüssel zu deinem Konto. Gib sie nie weiter und füge sie nie in einen Chat ein.

Du brauchst

  • npmNode.js installiert (für den Befehl npx)

Welche App nutzt du?

Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.

Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein

{
  "mcpServers": {
    "brainllm": {
      "command": "npx",
      "args": [
        "-y",
        "brainllm"
      ],
      "env": {
        "TRILIUM_BASE_URL": "your-value",
        "TRILIUM_ETAPI_TOKEN": "your-value",
        "TRILIUM_PASSWORD": "your-value",
        "BRAINLLM_MODE": "your-value",
        "BRAINLLM_TZ": "your-value",
        "BRAINLLM_OWNER_PASSWORD": "your-value",
        "BRAINLLM_OAUTH_SECRET": "your-value",
        "BRAINLLM_PUBLIC_URL": "your-value",
        "BRAINLLM_ALLOW_UNAUTHENTICATED_HTTP": "your-value",
        "BRAINLLM_TRUST_PROXY": "your-value"
      }
    }
  }
}

Führe das in deinem Terminal aus

claude mcp add brainllm --env TRILIUM_BASE_URL=your-value --env TRILIUM_ETAPI_TOKEN=your-value --env TRILIUM_PASSWORD=your-value --env BRAINLLM_MODE=your-value --env BRAINLLM_TZ=your-value --env BRAINLLM_OWNER_PASSWORD=your-value --env BRAINLLM_OAUTH_SECRET=your-value --env BRAINLLM_PUBLIC_URL=your-value --env BRAINLLM_ALLOW_UNAUTHENTICATED_HTTP=your-value --env BRAINLLM_TRUST_PROXY=your-value -- npx -y brainllm

Trag die leeren Werte ein, bevor du ihn startest.

In Cursor öffnen

Oder kopier die Einstellungen selbst

In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen

{
  "mcpServers": {
    "brainllm": {
      "command": "npx",
      "args": [
        "-y",
        "brainllm"
      ],
      "env": {
        "TRILIUM_BASE_URL": "your-value",
        "TRILIUM_ETAPI_TOKEN": "your-value",
        "TRILIUM_PASSWORD": "your-value",
        "BRAINLLM_MODE": "your-value",
        "BRAINLLM_TZ": "your-value",
        "BRAINLLM_OWNER_PASSWORD": "your-value",
        "BRAINLLM_OAUTH_SECRET": "your-value",
        "BRAINLLM_PUBLIC_URL": "your-value",
        "BRAINLLM_ALLOW_UNAUTHENTICATED_HTTP": "your-value",
        "BRAINLLM_TRUST_PROXY": "your-value"
      }
    }
  }
}

Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.

In VS Code öffnen

Oder kopier die Einstellungen selbst

In .vscode/mcp.json in deinem Projekt einfügen

{
  "servers": {
    "brainllm": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "brainllm"
      ],
      "env": {
        "TRILIUM_BASE_URL": "your-value",
        "TRILIUM_ETAPI_TOKEN": "your-value",
        "TRILIUM_PASSWORD": "your-value",
        "BRAINLLM_MODE": "your-value",
        "BRAINLLM_TZ": "your-value",
        "BRAINLLM_OWNER_PASSWORD": "your-value",
        "BRAINLLM_OAUTH_SECRET": "your-value",
        "BRAINLLM_PUBLIC_URL": "your-value",
        "BRAINLLM_ALLOW_UNAUTHENTICATED_HTTP": "your-value",
        "BRAINLLM_TRUST_PROXY": "your-value"
      }
    }
  }
}

Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.

Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.

Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.

Werte, die du selbst einträgst

  • TRILIUM_BASE_URL erforderlich env
    Base URL of the TriliumNext instance, e.g. http://localhost:8080
  • TRILIUM_ETAPI_TOKEN geheim env
    ETAPI token. Required unless TRILIUM_PASSWORD is set. Create one in Trilium under Options → ETAPI.
  • TRILIUM_PASSWORD geheim env
    Alternative to TRILIUM_ETAPI_TOKEN — BrainLLM mints a token on first start and caches it beside brainllm.json.
  • BRAINLLM_MODE env
    core (default) exposes the 45 brain-aware tools; full additionally exposes the 33 raw ETAPI tools.
  • BRAINLLM_TZ env
    IANA timezone used to stamp dated notes, e.g. Africa/Johannesburg. Defaults to the host timezone.
  • BRAINLLM_OWNER_PASSWORD geheim env
    Enables the OAuth 2.1 / CIMD endpoints required by claude.ai and other hosted Claude surfaces. This is the password entered on the consent screen when authorizing a client.
  • BRAINLLM_OAUTH_SECRET geheim env
    Optional 32+ character deployment secret for signing OAuth tokens; rotate it to invalidate old tokens.
  • BRAINLLM_PUBLIC_URL env
    Override for the public origin when a proxy rewrites Host. Must exactly match the URL entered in the client.
  • BRAINLLM_ALLOW_UNAUTHENTICATED_HTTP env
    Explicit trusted-network-only escape hatch for HTTP mode. Never enable on a public interface.
  • BRAINLLM_TRUST_PROXY env
    Trust forwarded host/protocol headers for OAuth discovery only when a trusted reverse proxy sets them.

Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.

Was er kann

Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.

Basischecksi

Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 6. Nov. 2026

  • ✓ Bestanden

    Entwickler passt zum Repo

    Der Registry-Name wurde mit dem GitHub-Konto miisodev bestätigt, dem das Repo gehört

  • … Noch nicht geprüft

    Wird noch gepflegt

    Dieses Repo haben wir noch nicht von GitHub gelesen

  • … Noch nicht geprüft

    Hat eine Lizenz

    Dieses Repo haben wir noch nicht von GitHub gelesen

  • – Nicht zutreffend

    Endpunkt antwortet

    Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet

  • – Nicht zutreffend

    Anmeldung mit OAuth

    Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen

  • … Noch nicht geprüft

    Keine versteckten Anweisungen in Tool-Beschreibungen

    Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen

Im Vergleich mit anderen in Suche & KI-Gedächtnisi

  • Mehr Sterne als 0 % der anderen 7234 Server in dieser Kategorie
  • Neuer in der Registry veröffentlicht als 93 % der anderen 7234 Server in dieser Kategorie
  • Basischecks gleich gut wie oder besser als bei 100 % der anderen 7234 Server in dieser Kategorie

Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.

Häufige Fragen

Ist Brainllm sicher?

Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.

Welche Schlüssel oder Codes braucht er?

Das musst du eintragen: TRILIUM_BASE_URL, TRILIUM_ETAPI_TOKEN, TRILIUM_PASSWORD, BRAINLLM_OWNER_PASSWORD, BRAINLLM_OAUTH_SECRET

Läuft er auf meinem Computer oder in der Cloud?

Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).

Wird er noch gepflegt?

Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (13.3.1) kam vorgestern in die Registry.

Welche Apps können ihn nutzen?

Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Node.js auf deinem Computer.

Was kann ich stattdessen nutzen?

In derselben Kategorie: Context7, Codebase Memory, Exa

Alternativen

Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.

So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti

Context7

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Codebase Memory

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

Läuft auf deinem Computer★ 48.148MITAktualisiert vor 20 Tagen
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Connect AI agents to Exa for web search, content fetching, and multi-step research.

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README vom Entwickler

README öffnen

Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.

BrainLLM

Give Claude a memory that survives the session.

Self-hosted memory for LLMs in TriliumNext Notes, structured by the server and editable by you, served over the Model Context Protocol.

Site · Connect to Claude · How it works · Docs · Privacy


What is BrainLLM?

LLMs forget. Every session starts from zero: who you are, what you're working on, what was decided yesterday, what went wrong last week. BrainLLM fixes that.

BrainLLM is an MCP server that gives an LLM a real, persistent memory — stored in TriliumNext Notes, a mature open-source knowledge base you self-host and own. The model opens each session by loading who you are and what's live, writes durable facts the moment they surface, wires knowledge together as a typed graph, and closes each session with a log, a diary entry, and a database backup. The next session picks up exactly where the last one ended.

It's a single Bun/TypeScript service with two dependencies (the MCP SDK and Zod), speaking to Trilium exclusively through its public ETAPI. Your memory lives in *your* Trilium instance — inspectable, editable, and portable, never locked inside a vendor's black box.

Who it's for

Anyone running an LLM as a long-running collaborator, not a one-shot Q&A tool — across coding, research, personal knowledge management, or day-to-day operational tracking — who wants that collaborator to actually remember: who you are, what's in flight, what was decided, without you re-explaining it every session. If you're comfortable self-hosting one small service and a Trilium instance, BrainLLM turns "the model forgot everything again" into a solved problem. It works with any MCP-capable client (Claude Desktop, Claude Code, or anything else speaking MCP), not just one product.

From experiment to open source

BrainLLM began in February 2026 as a personal experiment: could an LLM operate a real, self-hosted memory reliably enough to be trusted as its own memory — orienting, writing, connecting, and closing sessions without a human doing the filing? Through sustained daily, production use the answer held. The design has settled, the failure modes have been found and fixed, and the project has graduated from experiment to something efficient and stable enough to share — so it's now open source. It still runs the author's own sessions every day; what you're reading is the same code, not a demo. It also still carries the shape of one person's daily use — see Adapting to your environment for exactly what that means and what to change.

The core principle

The model supplies content. The server owns form.

Placement, naming, labels, deduplication, relation bookkeeping, lifecycle aging, archival, date stamping, HTML sanitization, backups — and structure itself — are all deterministic server policy, never delegated to the LLM. The model never chooses a parent note, never sets a label, never checks for duplicates, never stamps a date. That division is what makes the memory *reliable*: every guarantee is enforced at the tool layer, not requested via prompt.

Design highlights
  • Structure is enforced, not requested — every content kind has a canonical structure, served by template() and held on write: a new thread requires its goal, thread/diary/session entries open with an identification line (which LLM, which environment, which session type), threads carry exactly one Resolution (owned by resolve()), duplicate section headings are detected, and Last updated stamps are server-maintained.
  • Domains born complete — creating a knowledge domain creates its book *and* its canonical Sources note (marker legend, stamp, grouped source list, revision table), so every claim has a sourcing home from the first write.
  • A visible graph — graph() renders the whole relation graph (or any note's neighborhood) as a Mermaid flowchart, maintained as a native Trilium note.
  • Byte-preserving artifacts — text is UTF-8, while binary content uses strict standard base64 in the tool contract and raw bytes on the wire; binary reads return an explicit MIME/base64 envelope instead of replacement characters.
  • One-call day orientation — day() serves the previous session, its change log and everything touched since in a single call.
  • Two thread shapes — a thread is a dated journal (one child per active day) or a titled collection (one maintained note per item, e.g. an ideas list), chosen once with shape= at creation.
  • Timeless notes, dated records — knowledge, information and thread books hold no state or history (only a domain's *Current State* does); maintain(deep=true) flags dated prose that creeps in. Every note except a log carries an icon, set by kind and backfilled by the sweep.
  • Resilient plumbing — every backend call is timeout-bounded with retry on idempotent reads; routine core writes are idempotent or duplicate-guarded, while full-mode raw overwrites remain explicit; content surgery survives the editor's own HTML rewriting; renaming a domain cascades to everything inside it; the maintenance sweep heals drift it finds.
  • Multi-agent by default — all write-classified tools serialize behind a process-wide FIFO lock, so two agents (an interactive session and an automated run, say) writing through one hosted instance queue in arrival order instead of racing; reads stay fully parallel. Deletion catch-up in the daily log keeps a note deleted after its day's close from vanishing without a trace — and its window is configurable (deletionCatchupDays in the lifecycle policy), defaulting to Trilium's 7-day retention.
  • Ask in prose, split on a seam — consistency(subject="…") finds every note asserting about a fact however it is phrased, no regex guessing; consistency(pattern, staleAfterDays=N) surfaces figures held in exactly one untouched note, the ones that rot silently because nothing disagrees with them, and skips sessions and diaries, which are history rather than claims; diff(since="today") reviews every note a session changed in one call; revise(find="Phase 2", within="tr") edits, inserts or removes a table row named by a few words inside it; read(ids=[…]) batches a multi-note orientation into one round trip — each note's size up front, or a single section= across them; and split(noteId, sections=[…], into="…") is the write half of the oversized-note problem — it lifts whole sections into a new note and leaves a pointer back. Information notes can carry a #mandate marker so a scoped session finds the one note it must obey without reading every note's prose.
  • A distinct connector identity — hosted instances advertise BrainLLM and their own origin, with same-origin PNG/SVG icons, explicit page favicon links and a real multi-size ICO. The canonical mark is shared across the connector, consent pages and public assets.
  • Preview changes and measure coverage — revise(noteId, edits=[…], dryRun=true) shows sequential match counts and sanitized before/after content with no revision, labels or gate writes. Revision failures stop content overwrites. consistency() reports read failures and scan coverage; case-insensitive comparisons retain spelling variants without false conflicts. Incomplete scans cannot establish absence or unanimity.
  • Registers close in one call — revise(find, within="tr", mode="remove", closure={thread, body}) removes a register row and records its closure in that thread's entry for the day, closure={note, table?, row?} moves a row into an explicitly selected register table; destination cells must match the table's shape. Destination-first ordering preserves recoverability, and moves=[{find, row?}] batches closures with preflight and per-row progress, and append={table, row} adds a row with no anchor to find; within= also accepts a row as a reader sees it ("Phase 2 | Claude | Open"), and a table row whose cells disagree with its header is flagged at write time and by maintain(deep).
  • Bulk edits and lighter receipts — revise(find, within="tr", mode="remove", all=true) removes every row an anchor sits in, in one write and previewable with dryRun=true; remember(kind="sources", revision=[{source, from}]) renames a Sources key when a source moves instead of adding a second row; a dated-thread append returns previousRun, its author's previous block and run number; read(ids, sizes=true) plans a bulk read from sizes and section sizes alone; and diff(since="today", summaryOnly=true) lists what changed without the lines.
  • Records you can prove — sessions, diary entries and dated thread entries are append-only, and now verifiably so: every close() seals its day's records into a digest chained to the previous day's, and maintain(deep) reports any sealed record that was rewritten afterwards. Appends stay legal; edits to history do not go unnoticed.

How it works

At bootstrap, BrainLLM builds a five-area tree in Trilium. Every note the tools create is typed, labeled, dated, and placed by server policy:

BrainLLM  (#brainLlmRoot)

├── 👤 Master Biography · Goals · Preferences (the user — maintained singletons) ├── 🤖 LLM Responsibilities · Protocols · Self-correction · Diary/ (the assistant's self-model + daily diary) ├── 🗂️ Memory Sessions/ · Threads/ (daily session logs + multi-session work) ├── 📚 Knowledge Master/ · Domains/ /{ Sources, info } (learned facts beyond/contra training) └── 💡 Insights Logs/ · Graph · Claims (the brain's record of itself)

Note classKindsBehavior
Singletonsbiography, goals, preferences, responsibilities, protocols, selfcorrection (+ each domain's Sources note)Exactly one maintained note; edited in place; hold *current-state truth*
Authored recordsdiary, session, dated threadEntryOne per calendar day and parent; every write lands as a timestamped addendum block — chronology is the point
Generated logslogOne per calendar day; regenerated in place from the change feed
Collectionsthread, user, information, domainTitled notes, deduplicated by normalized title within their scope

A session follows an enforced protocol: start() orients (who you are, live threads, what changed since last time) → the model works, writing durable facts *as they surface* → session() → addendum() → maintain() → remarks() → diary() → `close

Nur der Anfang wird gezeigt; den Rest findest du im Repo

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