memex

memex

Persistent note storage for AI agents. Memex lets your assistant save, search, and retrieve memories across sessions — acting as a durable second brain that outlives any single conversation.

Category
访问服务器

README

memex

npm license node

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

npm install -g @evan-moon/memex

Connect to Claude Code:

memex mcp install

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


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
  • MCP server — Claude searches and saves automatically. No extra CLAUDE.md setup needed
  • 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

# Add notes
memex add                                    # interactive prompt
memex add --title "Note title" --content "..."
memex add --title "Note title" --file ./note.md
memex add --title "Note title" --content "..." --folder conversations/tom
memex add --title "Note title" --content "..." -T typescript -T architecture

# Search
memex search "semantic search query"         # multilingual
memex search "지식 관리" --limit 10
memex search "query" --tag typescript        # filter by tag

# Browse
memex list                                   # recent 10 notes
memex list --limit 20
memex show <id>
memex tags                                   # all tags with counts
memex related <id>                           # semantically related notes

# Edit / delete
memex edit <id>
memex delete <id>
memex delete --yes <id>                      # skip confirmation

# Index external directories
memex source add ~/Documents/My\ Notes       # register a vault
memex source list
memex source remove ~/Documents/My\ Notes
memex index                                  # scan vault + all sources
memex index --force                          # re-index everything
memex reembed                                # re-embed with current model

# Config
memex config show
memex config set vault-path ~/Documents/Second\ Brain

# MCP
memex mcp install                            # register with Claude Code
memex mcp path                               # print MCP binary path

MCP server

Claude Code

memex mcp install

Or manually:

claude mcp add memex -- node "$(memex mcp path)"

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "memex": {
      "command": "node",
      "args": ["<path from `memex mcp path`>"]
    }
  }
}

Available tools

Tool Description
save_note Save a note with title, content, folder, and tags
search_notes Semantic search across all notes
list_notes List recent notes
get_note Get full content of a note by ID
update_note Update title or content of an existing note
delete_note Delete a note by ID

Configuration

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

Key Default Description
vault_path ~/Documents/Second Brain Directory where .md files are saved
sources [] Additional directories to index (e.g. existing Obsidian vaults)
aliases {} Search alias map, e.g. { "js": ["javascript", "자바스크립트"] }
memex config set vault-path ~/my-vault

Architecture

~/.memex/
  config.json       — vault path, sources, and aliases
  memex.db          — SQLite DB (notes + vec embeddings + FTS5 index)
  models/           — cached embedding model

<vault>/
  *.md              — notes (Obsidian-compatible)
Package Role
@memex/db SQLite schema, drizzle queries, sqlite-vec + FTS5 integration
@memex/embed Local embedder via @huggingface/transformers
@memex/utils Config, path helpers, shared utilities
@memex/mcp MCP server (bundled into CLI dist)

Part of a personal AI stack

memex is the memory layer of the Herald ambient voice assistant stack.

Herald + memex + Firma — ambient voice, persistent memory, and financial intelligence.


License

MIT

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选