Memex

io.github.evan-moonPublished by GitHub account evan-moonv0.5.0Updated Oct 24, 2026

Local-first second brain with semantic search. Markdown notes indexed by a local ML model.

VerifiedSTDIODesktop onlyFiles & StorageKnowledge & Memory

Overview

AI-generated overview

Local-first Markdown note vault with offline semantic search, letting an assistant save, search, read and update notes as long-term memory.

What you can do
  • Save notes with a layer (past, state or rule), with duplicate warnings and related-note flashbacks
  • Search notes semantically with tag, folder and date filters, and list recent notes, tags and folders
  • Read a note's full content and backlinks, update titles or content, and delete notes
  • Review deterministic signals and synthesized inferences, and mint an approved inference
When to use it
Useful when you want an assistant to recall your own decisions, plans and context across sessions without pasting them into every conversation, and you prefer notes kept as plain Markdown files on your machine.
Requirements
Runs as a local process installed from the npm package @evan-moon/memex (Node.js). First run downloads an embedding model of about 450MB to ~/.memex/models/. Notes and a SQLite database live under ~/.memex/. No API keys or accounts are needed.
Before you install
The assistant can write, update and delete notes in your vault, and rule-layer notes are injected into its instructions on every conversation. Optional auto-recall sends note titles into each prompt as context. Optional reranking is enabled with MEMEX_RERANK=1. Data stays local; nothing is sent to third parties.

Installation

In SourceWeft

  1. Open Memex in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

[memex]

memex

Make Claude smarter about you.

[npm version] [License] [Node version]

npm install -g @evan-moon/memex

Make Claude smarter about you.

Local-first second brain that connects to Claude via MCP. Notes are stored as plain Markdown and indexed with a local ML model, fully offline, no API keys, nothing leaves your machine.


The problem

Claude is only as smart as what's in the conversation. Your decisions, your context, your thinking, invisible unless you paste them in every time.

You:    What did we decide about the auth approach last sprint?Claude: I don't have context from previous conversations...

The fix

You:    What did we decide about the auth approach last sprint?
Claude: [memex · search_notes · "auth approach decision"]
        Found 2 notes:
        Auth Architecture Decision  Apr 14  #auth #backend        ─────────────────────────────────────────────────────        Chose JWT + refresh tokens over sessions. Rationale:        stateless design fits horizontal scaling plan.
        Based on your April 14th note: you went with JWT +        refresh tokens. Tom also flagged keeping auth decoupled        from payment logic, separate bounded contexts.

Claude searches your notes before answering and saves insights at the end of every conversation, automatically, without being asked.


Install

bash
npm install -g @evan-moon/memex

Connect your apps:

bash
memex mcp install

This registers memex with every MCP client on this machine — Claude, Claude Code, Codex, Cursor — by writing each one's own config file. Restart the clients afterwards.

That's it. On first run, the embedding model (~450MB) downloads once to ~/.memex/models/.

Auto-recall (optional)

bash
memex recall install

Turns retrieval from something Claude has to decide to do into something that just happens. Every prompt you type is semantically searched against your notes, and the top 3 titles are injected as context before Claude answers — the same way native memory works. Claude then pulls full notes with get_note when a title looks relevant.

A background daemon keeps the embedding model warm (~/.memex/recall.sock), so a lookup costs ~30ms instead of the ~1.5s a cold CLI search spends loading the model. It idles out after 2 hours.

Cost: ~200MB resident while warm, plus up to 3 note titles of context per prompt. Remove with memex recall uninstall.


Features

  • Semantic search, finds notes by meaning, not just keywords. Multilingual (Korean + English), runs fully offline via multilingual-e5-base
  • Hybrid retrieval, vector search + BM25 full-text + tag matching, fused via Reciprocal Rank Fusion
  • Chunk-level embeddings, long notes are split into ~340-token passages and embedded individually, so an answer buried on page three is as findable as one in the opening paragraph. Search returns the passage that matched, not the note's first lines
  • Cross-encoder reranking (opt-in, MEMEX_RERANK=1), retrieves twice as many candidates and reorders them with bge-reranker-v2-m3. Worth ~+20pp hit@1 on the golden set, at ~1.8s per search — off by default because auto-recall and the CLI are built around instant lookups
  • Date filter, narrow search to a time range with --from / --to
  • Note layers, every note is past (immutable record), state (mutable plan), or rule (Claude behaviour guide). Past notes refuse updates; rule notes auto-inject into Claude's system prompt
  • Flashback, save and search automatically surface older notes from a different folder that are semantically related, "you wrote about this 124 days ago in a different context"
  • Inference engine, deterministic signals surface un-synthesized patterns (cross-year arcs, stale state notes, tag revivals); you promote good ones into inferences (hypotheses with provenance) that auto-invalidate when their source notes change. No LLM in the core
  • MCP server, Claude searches and saves automatically. No extra CLAUDE.md setup needed
  • Auto-recall, opt-in hook that searches your notes on every prompt and injects the hits before Claude answers, so recall never depends on Claude remembering to look
  • Duplicate detection, save_note warns when a semantically similar note already exists, nudging Claude to update rather than create
  • Backlinks, link notes with [[Title]] syntax; get_note shows which notes reference it
  • Series collapse, a dated work log ("… 2026-07-20", "… 2026-07-23") takes at most two slots on a result page, and search reports how many more it held back
  • Amendments, a correction records what it corrects (amends), so search flags the superseded note and points at the newest fix instead of returning a claim you already know is wrong
  • Digest, memex digest summarises notes saved in the last N days, grouped by folder
  • CLI, add, search, tag, browse, and index notes from the terminal
  • Obsidian-compatible, notes saved as .md files; works alongside existing vaults
  • Local DB, SQLite + sqlite-vec at ~/.memex/memex.db

CLI

bash
# Add notesmemex add                                    # interactive prompt (asks for layer)memex add --title "Note title" --content "..." --layer pastmemex add --title "Note title" --file ./note.md --layer statememex add --title "Note title" --content "..." --folder work/people/tom --layer pastmemex add --title "Note title" --content "..." -T typescript -T architecture --layer past
# Layersmemex layer                               # distribution of past / state / rulememex layer <id> state                     # move a note to a different layer
# Searchmemex search "semantic search query"         # multilingualmemex search "knowledge management" --limit 10    # multilingual: matches Korean/Japanese notes toomemex search "query" --tag typescript        # filter by tagmemex search "query" --from 2026-04-01       # notes since a datememex search "query" --from 2026-04-01 --to 2026-04-30
# Browsememex list                                   # recent 10 notesmemex list --limit 20memex show <id>memex tags                                   # all tags with countsmemex related <id>                           # semantically related notesmemex digest                                 # last 7 days + signals + inferencesmemex digest --days 30                       # summary of last 30 days
# Insights (inference engine)memex signals                                # detect un-synthesized patternsmemex signals --type hidden_arc              # one type onlymemex signals dismiss <id>                   # triage (also: snooze)memex signals mint <signalId>                        # print evidence bundle to synthesizememex signals mint <signalId> --title "..." --summary "..." --confidence 0.7memex inferences                             # list inferences (auto-flags stale)memex schedule                               # print cron/launchd snippet (no daemon)
# Edit / deletememex edit <id>memex delete <id>memex delete --yes <id>                      # skip confirmation
# Index external directoriesmemex source add ~/Documents/My\ Notes       # register a vaultmemex source listmemex source remove ~/Documents/My\ Notesmemex index                                  # scan vault + all sourcesmemex index --force                          # re-index everythingmemex reembed                                # re-embed with current model
# Configmemex config showmemex config set vault-path ~/Documents/Second\ Brain
# MCPmemex mcp install                            # register with every MCP client on this machine
# Auto-recallmemex recall install                         # search notes on every prompt, inject hitsmemex recall uninstall                       # remove the hookmemex mcp path                               # print MCP binary path

MCP server

Claude, Claude Code, Codex, Cursor

bash
memex mcp install

It writes each client's own config file and leaves the servers already in it alone. If a client still runs an older copy of memex, it gets repointed. memex mcp path prints the server path for a client memex does not know about yet.

Available tools

ToolDescription
save_noteSave a note, requires layer, warns if a similar note already exists, surfaces flashbacks
search_notesSemantic search; supports category, tag, date_from, date_to filters; appends flashbacks for the top result
list_notesList recent notes
list_tagsList all tags with note counts
list_foldersList all folders with note counts
get_noteGet full content and backlinks of a note by ID
update_noteUpdate title or content. Refuses past notes (with [Amendment] suggestion) and rule notes (user-only)
delete_noteDelete a note by ID
get_signalsDeterministic un-synthesized patterns (hidden_arc / stale_state / dangling_link / tag_burst)
update_signal_statusTriage a signal, dismiss or snooze
list_inferencesList synthesized hypotheses (re-checks staleness first)
get_inferenceOne inference with full provenance + change/delete markers
mint_inferencePersist an approved hypothesis, requires explicit confirmation

Inferences are kept separate from notes (excluded from search) and are cited as hypotheses, never facts. Detection stays deterministic; the only LLM step is synthesizing an inference's summary, which Claude does, never memex.

Note layers

Every note is classified into one of three layers based on mutability:

LayerMeaningClaude's permission
pastRecord of what happened, retros, meetings, decision rationale, debugging sessionsAppend-only. update_note refuses, suggesting an [Amendment] note instead
stateCurrent state or plans, project progress, roadmaps, a person's current roleFreely updatable
ruleBehaviour guide for Claude, coding style, search policyClaude is read-only. Only the user writes

The CLI prints a colour-coded [past] / [state] / [rule] badge next to each note in list, search, and show.

  • save_note (MCP) and memex add (CLI) require an explicit layer. The classification rules are documented in the tool description so Claude picks correctly.
  • On first run, existing notes get a folder-based backfill: projects/dev/herald → state, coding → rule, everything else → past. Migration is idempotent.
  • rule notes are also auto-injected into the MCP server's instructions, see Rule layer auto-inject below.

Flashback

When you save a note or search, memex automatically surfaces older notes from a different folder that are semantically similar, "you wrote about this 124 days ago in a different context." Stored as system-generated backlinks (note_links.source = 'flashback'), separate from your [[wikilinks]] (source = 'wiki').

Tune via env:

EnvDefaultBehaviour
MEMEX_FLASHBACK_DAYS90minimum age gap, in days
MEMEX_FLASHBACK_DIST0.4maximum vector distance (lower = stricter match)
MEMEX_FLASHBACK_LIMIT3max suggestions per surface

Rule layer auto-inject

Notes with layer = 'rule' are appended to the MCP server's instructions on boot, under a ## House Rules section. Claude sees them at the start of every conversation, no search_notes call required. This is the right home for coding style guides or other behavioural guidance.

EnvDefaultBehaviour
MEMEX_INJECT_RULESenabledSet to 0 to disable injection entirely
MEMEX_RULES_MAX_CHARS8000Byte budget for the injected section; overflow is truncated with a console.warn

Updates to rule notes are picked up on the next Claude Desktop / Claude Code restart.


Configuration

Config lives at ~/.memex/config.json.

KeyDefaultDescription
vault_path~/Documents/Second BrainDirectory where .md files are saved
sources[]Additional directories to index (e.g. existing Obsidian vaults)
aliases{}Search alias map, e.g. { "js": ["javascript", "ecmascript"] }, values can be any language to bridge across scripts
bash
memex config set vault-path ~/my-vault

Architecture

~/.memex/  config.json, vault path, sources, and aliases  memex.db, SQLite DB (notes + note/chunk vec embeddings + FTS5 index)  models/, cached embedding model
<vault>/  *.md, notes (Obsidian-compatible)
PackageRole
@memex/dbSQLite schema, drizzle queries, sqlite-vec + FTS5 integration
@memex/embedLocal embedder via @huggingface/transformers
@memex/rerankLocal cross-encoder reranker (opt-in)
@memex/coreNote service shared by CLI and MCP: save, edit, search, vector indexing
@memex/utilsConfig, path helpers, shared utilities
@memex/mcpMCP server (bundled into CLI dist)

The ecosystem

memex is one of three local-first tools that share one principle, your data stays on your machine, and the AI comes to it. They interoperate through any MCP client, and none depends on the others.

mermaid
flowchart TB    U([You])    subgraph I["Interfaces, talk to your tools"]        direction LR        CD[Claude Desktop]        CC[Claude Code]        CU[Cursor]    end    subgraph T["Local-first tools, each owns its data, on your machine"]        direction LR        F["firma · money<br/>~/.firma"]        M["memex · memory<br/>~/.memex"]        S["skope · news<br/>~/.skope"]    end    U --> I    I -- MCP --> F & M & S    F <-. never call each other .-> M    M <-.-> S
  • firma · money, portfolio, net worth, cash flow
  • memex · memory, notes and the context behind them, across sessions
  • skope · news, a personalized lens on the world

You reach them through Claude Desktop, Claude Code, Cursor, or any other MCP client. The tools compose through the model, never by calling each other.


Where this is going

memex is a memory engine, not a place to read. There is no window, no editor, and no screen to keep up with. Everything a person would have supervised by hand — what is still true, what a later note corrected, which notes answer a question nobody phrased the way they were written — has to be settled by the retrieval path itself, at the moment an agent asks.

The reasoning behind dropping the desktop app: a document an LLM wrote is a document nobody reads. A vault that needs curating is a vault that rots. So the target is a structure that retrieves correctly without being read and without being maintained:

GoalStatus
Retrieval that answers the question, not the phrasing (hybrid + rerank + chunking)shipped
A correction reaching every surface that returns the note it correctedshipped
Signals and inferences that name what went stale, deterministicallyshipped
Layers and templates that make a note's lifetime explicit at write timeshipped
Staleness settled at read time rather than by a person clearing a queuein progress
Evidence (derives_from) required, so a claim can be rechecked without guessingin progress

Out of scope: a GUI, sync, collaboration, publishing, a plugin system, and a graph canvas.

The design record is in docs/plans/. Those documents are a history of decisions, not a roadmap, and the ones written for the desktop app have been removed.


llms.txt

llms.txt is a machine-readable summary of this project for LLM agents, concise description with documentation links, following the llms.txt standard.


License

MIT

Source: README.md at commit 19aae2c

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v0.5.0LatestSep 16, 2026

Score

50% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts

    Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.

  • Auth declared10 pts

    Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.

  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts