basic-memory 0.21.0

Local-first knowledge management combining Zettelkasten with knowledge graphs

Skip the install — try Basic Memory in the cloud

Claude, Codex, or Cursor connected in 30 seconds. No Python, no JSON, no terminal. $14.25/mo locked in for life (regular price $19). 7-day free trial — cancel any time before day 7 if it's not for you. Beta pricing — sign up now and your rate never goes up. OSS users: code BMFOSS takes another 20% off for 3 months.

Start free trial →

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Basic Memory

Your AI never forgets again.

Pick up right where you left off — in Claude, Codex, Cursor, ChatGPT, or anything that speaks MCP. Your knowledge lives as Markdown files that both you and your AI can read, write, and search.

• Local-first. Plain text on your disk. Forever.
• Two-way. AI and humans write to the same files; sync keeps them in step.
• A real knowledge graph. Observations and wikilinks compound into context.
• Semantic search. Find notes by meaning, not just keywords.
• MCP-native. Works with every major AI client and IDE.
• Progressive tool discovery. Every tool is tagged with behavior hints (read-only, destructive, idempotent) so agents pick the right tool on demand — no wasted context trying things to see what they do.
• Cloud, optional. Sync across devices when you want — never required.

Get started

Pick the path that fits you. Both run the same product on the same Markdown.

☁️   Cloud	💻   Local install
30 seconds. Sign up, connect your AI client, done. Works in any browser Mobile, web, desktop Cross-device sync built in We handle hosting, backups, snapshots $14.25/mo locked for life · 7-day free trial · cancel any time Start free trial →	2 minutes. Install, configure your AI client, run. Free forever (AGPL-3.0) All data on your disk Air-gapped friendly Requires Python via uv uv tool install basic-memory Configure your client ↓

What people are saying

Basic Memory changed my whole relationship with LLMs. I switched from GPT and Gemini to exclusively Claude and Claude Code because of this integration and am completely revamping all our company's processes around a Basic Memory workflow.

— Alex, TrainerDay

Basic Memory is the missing 'wow' factor in AI chatbots. Now I can't imagine Claude or Claude Code without it.

— Caleb, Caleb Picker Consulting

I don't code without Basic Memory anymore. It's such a time saver to be able to refer to projects I don't currently have active and keep a running log of all my learnings and ProTips.

— @groksrc, Developer

More on basicmemory.com.

Basic Memory Cloud

The hosted version of Basic Memory. Same product, same Markdown files, same MCP tools — we just host the database, run the sync, and put it on your phone.

What you get

• Every device, same brain. Your knowledge graph on web, mobile, and desktop. No copy-paste between machines.
• Connect any MCP client. Claude Desktop, Claude Code, Codex, Cursor, ChatGPT (Custom GPTs), VS Code — one-click connect from the web app.
• Bidirectional sync to local. Edit on your phone, see it in Obsidian on your laptop. rclone-powered with conflict resolution.
• Snapshots and backups. Point-in-time restore. Browse history. Never lose a note.
• No lock-in. Your notes are plain Markdown. Export to local Markdown any time — same files, same format, same wikilinks. Cancel anytime, your data stays yours.

Built on WorkOS AuthKit, Neon Postgres, and Tigris S3. Platform source at basic-memory-cloud.

Pricing

$14.25/mo, locked in for the life of your subscription (regular price $19). Sign up during beta and the rate never goes up — as long as you stay subscribed, you keep the price. One plan, no tiers, no surprise upgrades. Unlimited notes, unlimited projects, every feature.

• 7-day free trial. Cancel any time before day 7 if it's not for you.
• Cancel anytime after that too — export your notes whenever you want.
• OSS users: code BMFOSS for another 20% off for 3 months (~$11.40/mo).

Start your 7-day free trial →

Cloud vs. local

	Cloud	Local
Setup time	30 seconds	2 minutes (requires Python)
Cost	$14.25/mo, locked for life (7-day trial)	Free
Storage	We host (Tigris S3)	Your disk
Cross-device sync	Built in	Manual (Git, Syncthing, etc.)
Mobile access	Yes (web + app)	No
Air-gapped	No	Yes
Your data stays yours	Yes — export anytime	Yes — already there
Source code	AGPL-3.0	AGPL-3.0
Snapshots & backups	Built in	Roll your own

Both paths use the same OSS engine and the same Markdown files. There's no lock-in either way — flip between them when your needs change.

Works with the tools you already use

Client	Transport	Notes
Cloud web app	https	Sign in at basicmemory.com — no install
Claude Desktop	stdio/https	macOS / Windows / Linux
Claude Code	stdio/https	claude mcp add
Codex	stdio/https	OpenAI's coding agent
Cursor	stdio/https	.cursor/mcp.json
VS Code	stdio/https	Native MCP support
ChatGPT	https	Custom GPT actions (search / fetch)
Obsidian	—	Reads/writes the same Markdown directly
Anything MCP	stdio/https	If it speaks MCP, it works

Pick up where you left off

https://github.com/user-attachments/assets/a55d8238-8dd0-454a-be4c-8860dbbd0ddc

Connect your AI client

If you went the Cloud route, the web app walks you through client connect. The snippets below are for local installs.

Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "basic-memory": {
      "command": "uvx",
      "args": ["basic-memory", "mcp"]
    }
  }
}

Restart Claude Desktop. Notes live in ~/basic-memory by default.

Claude Code, Codex CLI, Cursor, VS Code, ChatGPT, Obsidian

Claude Code

claude mcp add basic-memory -- uvx basic-memory mcp

Codex CLI

Add to ~/.codex/config.toml:

[mcp_servers.basic-memory]
command = "uvx"
args = ["basic-memory", "mcp"]

Cursor

Add to .cursor/mcp.json (project) or ~/.cursor/mcp.json (global):

{
  "mcpServers": {
    "basic-memory": {
      "command": "uvx",
      "args": ["basic-memory", "mcp"]
    }
  }
}

VS Code

Add to your User Settings (JSON):

{
  "mcp": {
    "servers": {
      "basic-memory": {
        "command": "uvx",
        "args": ["basic-memory", "mcp"]
      }
    }
  }
}

ChatGPT

Basic Memory exposes OpenAI-compatible search and fetch tools for Custom GPT actions. See the ChatGPT integration guide.

Obsidian

No setup. Point Obsidian at ~/basic-memory (or your project folder) and the same wikilinks, frontmatter, and Markdown your AI writes appear in your graph view. Edit either side — sync handles the rest.

Try a prompt:

"Create a note about our project architecture decisions."
"Find information about JWT auth in my notes."
"What have I been working on this week?"

What's New

• Automatic updates. Basic Memory keeps itself up to date for uv tool and Homebrew installs; bm update triggers a manual check.
• Semantic vector search. Find notes by meaning, not just keywords. Hybrid full-text + vector ranking with FastEmbed embeddings, on SQLite or Postgres.
• Schema system. Infer, validate, and diff the structure of your knowledge base with schema_infer, schema_validate, schema_diff.
• Per-project cloud routing. Route individual projects through the cloud while others stay local, via API key (bm project set-cloud).
• Smarter editing. edit_note append/prepend auto-creates notes when missing; write_note guards against accidental overwrites.
• Richer search results. Matched chunk text is included so the LLM gets context, not just hits.
• FastMCP 3.0 + tool annotations. Every tool ships with MCP behavior hints (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) so agents can discover capabilities progressively at runtime instead of guessing or burning tokens.
• CLI overhaul. --json output for scripting, workspace-aware commands, and an htop-inspired project dashboard.

Full CHANGELOG for v0.18 → v0.20.

Why Basic Memory

Most LLM conversations are ephemeral. You ask a question, get an answer, then everything is forgotten. Workarounds have limits:

• Chat history captures conversations but isn't structured knowledge.
• RAG lets the LLM query your documents but not write back to them.
• Vector DBs need complex infra and usually live in someone else's cloud.
• Knowledge graphs need specialized tooling to maintain.

Basic Memory takes a simpler path: structured Markdown files that humans and LLMs both read and write.

• All knowledge stays in plain files you control.
• Both sides read and write to the same files.
• Familiar Markdown with semantic patterns — no new format to learn.
• A traversable graph the LLM can follow link by link.
• Works with the editors you already use (Obsidian, VS Code, anything).
• Just files plus a local SQLite index. No servers required.

How it works

You're chatting normally about coffee:

I've been experimenting with brewing methods. Pour over gives more clarity than French press, water at 205°F seems best, and freshly ground beans make a huge difference.

Ask the LLM to capture it:

"Make a note on coffee brewing methods."

A Markdown file appears in your project directory in real time:

---
title: Coffee Brewing Methods
permalink: coffee-brewing-methods
tags: [coffee, brewing]
---

# Coffee Brewing Methods

## Observations
- [method] Pour over highlights subtle flavors over body
- [technique] Water at 205°F (96°C) extracts optimal compounds
- [principle] Freshly ground beans preserve aromatics

## Relations
- relates_to [[Coffee Bean Origins]]
- requires [[Proper Grinding Technique]]
- affects [[Flavor Extraction]]

Next session, the LLM picks up the thread. It follows the relations to surface what you already know about Ethiopian beans and burr grinders, and builds on it instead of starting over. You see the same files in Obsidian or your editor. Edit them by hand — the AI sees your changes too.

Real two-way flow: humans edit Markdown, LLMs read/write through MCP, sync keeps everything consistent, and the source of truth is always your files.

The Markdown format

Each file is an Entity. Entities have Observations (facts about them) and Relations (links to other entities). That's the whole grammar.

Frontmatter

---
title: <Entity title>
type: note
permalink: <uri-slug>
tags: [optional, list]
---

Observations

Facts about the entity. Categories in [brackets], tags with #, optional context in parens.

- [method] Pour over highlights subtle flavors
- [tip] Grind medium-fine for V60 #brewing
- [fact] Lighter roasts contain more caffeine than dark
- [resource] James Hoffmann's V60 technique on YouTube
- [question] How does temperature affect compound extraction?

Relations

Wiki-style links that form the graph. Single-token relation types, or quote multi-word ones.

- pairs_well_with [[Chocolate Desserts]]
- grown_in [[Ethiopia]]
- requires [[Burr Grinder]]
- "pairs well with" [[Dark Chocolate]]

Bare - [[Target]] and prose - Worth checking out [[Target]] index as links_to. Full reference in the docs.

MCP tools

Basic Memory exposes these tools to any MCP client. Every tool is annotated with MCP behavior hints (read-only, destructive, idempotent, open-world) so agents can pick the right one without trial-and-error:

• Content: write_note, read_note, edit_note, move_note, delete_note, read_content, view_note
• Search & discovery: search, search_notes, recent_activity, list_directory
• Knowledge graph: build_context (navigates memory:// URLs), canvas (Obsidian canvas generation)
• Projects: list_memory_projects, create_memory_project, get_current_project, sync_status
• Schema: schema_infer, schema_validate, schema_diff
• Cloud: cloud_info, release_notes

All MCP tools default to text output; pass output_format="json" for structured responses. Full tool reference in the docs.

CLI essentials

# Projects
basic-memory project list
basic-memory project add research ~/research
basic-memory project set-cloud research   # route through cloud
basic-memory project set-local research   # revert

# Health & maintenance
basic-memory status
basic-memory doctor              # file <-> DB consistency check
basic-memory tool edit-note ...  # CLI access to MCP tools
basic-memory update              # check for and install updates

# Imports
basic-memory import claude conversations
basic-memory import chatgpt
basic-memory import memory-json

Routing flags (--local / --cloud) force a target when you're in mixed mode. Full CLI reference in the docs.

Auto-updates

CLI installs check for updates every 24 hours by default and apply them silently (so the MCP server keeps responding).

• Supported install sources: uv tool, Homebrew
• Skipped for uvx (ephemeral runtime managed by uv)
• Manual: bm update (check + apply) or bm update --check (check only)

Disable in ~/.basic-memory/config.json:

{ "auto_update": false }

Telemetry

Minimal, anonymous events to understand the CLI-to-cloud conversion funnel.

What we collect: cloud promo impressions, cloud login attempts and outcomes, promo opt-out events.

What we don't: file contents, note titles, knowledge base data, PII, IP addresses, per-command or per-tool tracking.

Events go to our Umami Cloud instance (open-source, privacy-focused) on a background thread — never blocks the CLI.

Opt out:

export BASIC_MEMORY_NO_PROMOS=1

This disables promos and all telemetry.

Logging

Basic Memory uses Loguru. Defaults vary by entry point:

Entry point	Default	Why
CLI commands	File only	Doesn't interfere with command output
MCP server	File only	Stdout would corrupt JSON-RPC
API server	File (local) or stdout (cloud)	Docker/cloud uses stdout

Log file: ~/.basic-memory/basic-memory.log (10MB rotation, 10 days retention).

Environment variables

Variable	Default	Description
BASIC_MEMORY_LOG_LEVEL	INFO	DEBUG / INFO / WARNING / ERROR
BASIC_MEMORY_CLOUD_MODE	false	API logs to stdout with structured context
BASIC_MEMORY_FORCE_LOCAL	false	Force local API routing
BASIC_MEMORY_FORCE_CLOUD	false	Force cloud API routing
BASIC_MEMORY_EXPLICIT_ROUTING	false	Mark route selection as explicit
BASIC_MEMORY_ENV	dev	Set to test for test mode (stderr only)
BASIC_MEMORY_NO_PROMOS	false	Disable cloud promos and telemetry
BASIC_MEMORY_IMPORT_UPLOAD_MAX_BYTES	104857600	Max uploaded import size

BASIC_MEMORY_LOG_LEVEL=DEBUG basic-memory sync
tail -f ~/.basic-memory/basic-memory.log

Development

Basic Memory supports SQLite (default, fast, no Docker) and Postgres (via testcontainers — Docker required).

just install          # Install with dev dependencies
just test-sqlite      # All tests, SQLite
just test-postgres    # All tests, Postgres (testcontainers)
just test             # Both backends
just fast-check       # fix/format/typecheck + impacted tests + smoke
just doctor           # File <-> DB consistency check (temp config)
just lint
just typecheck        # Pyright (primary)
just typecheck-ty     # ty (supplemental)
just format
just check            # All quality checks
just migration "msg"  # New Alembic migration

Tests use pytest markers: windows, benchmark, smoke. See justfile for the full list.

Contributions welcome — see CONTRIBUTING.md.

License

AGPL-3.0.

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