Prototype · Preview: every server in the official registry, synced every 30 minutes. Reviews and accounts come in a later step.
PopNx MCPMCP servers for people who use AI · explained in plain words

Brainllm

by miisodevversion 13.3.1i★ –iRuns on your computer
Registry nameio.github.miisodev/brainllm

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Search & AI memory
  • You need to fill in: TRILIUM_BASE_URL, TRILIUM_ETAPI_TOKEN, TRILIUM_PASSWORD, BRAINLLM_OWNER_PASSWORD, BRAINLLM_OAUTH_SECRET

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: 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

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "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"
      }
    }
  }
}

Run this in your terminal

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

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "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"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "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"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • TRILIUM_BASE_URL required env
    Base URL of the TriliumNext instance, e.g. http://localhost:8080
  • TRILIUM_ETAPI_TOKEN secret env
    ETAPI token. Required unless TRILIUM_PASSWORD is set. Create one in Trilium under Options → ETAPI.
  • TRILIUM_PASSWORD secret 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 secret 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 secret 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.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account miisodev, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

  • More stars than 0% of the other 7241 servers in this category
  • Published to the registry more recently than 93% of the other 7241 servers in this category
  • Basic checks equal to or better than 100% of the other 7241 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Brainllm safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: TRILIUM_BASE_URL, TRILIUM_ETAPI_TOKEN, TRILIUM_PASSWORD, BRAINLLM_OWNER_PASSWORD, BRAINLLM_OAUTH_SECRET

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (13.3.1) reached the registry 3 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated 3 days ago
Install

Codebase Memory

by DeusData

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

Runs on your computer★ 48,148MITUpdated 20 days ago
Install

Exa

by exa-labs

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

Runs in the cloud★ 5,213MITUpdated 44 days ago
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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

Only the beginning is shown; read the rest in the repo

Ask PopNx