basicmachines-co/basic-memory

Claude, Codex, or Cursor connected in 30 seconds. No Python, no JSON, no terminal. $15.00/mo locked in for life (12.50/mo yearly pricing). 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 →

Give your team a single, shared cloud workspace. Knowledge isn't confined to one person — anything a teammate writes is immediately available to everyone else and to their AI assistants. Edit a note together in real time, hand work off between humans and agents, and build one connected knowledge base instead of scattered copies. Same pricing - start with one user and add more as needed.

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, with optional cross-encoder reranking for higher-quality vector and hybrid results.
• 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.

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

uv tool install basic-memory --prerelease=allow

uv tool install "basic-memory[milvus]" --prerelease=allow

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.

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.

• 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.

$15.00/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 →

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.

This repository is also the canonical home for Basic Memory's host-native agent packages. The core Python package, Claude Code plugin, shared skills, Hermes plugin, and OpenClaw plugin all ship from the same source tree.

Maintainers can verify the whole consolidated surface from the repo root:

just package-check

Package-local justfiles are also available when working inside one host:

just package-check-claude-code
just package-check-skills
just package-check-hermes
just package-check-openclaw

The Claude Code plugin is the bridge between Claude's working memory and Basic Memory — session-start briefings, pre-compaction checkpoints, an opt-in capture output style, and /basic-memory:bm-setup · :remember · :share · :status.

Connect the Basic Memory MCP server first — see Connect your AI client. The plugin's hooks and skills call it, so it's a hard prerequisite. Then install the plugin:

bm install claude-code

That registers the marketplace and installs the plugin through Claude Code. Add --scope project to declare both in the repository's settings for a team, or --dry-run to see the underlying claude plugin commands without running them.

Source: plugins/claude-code.

Framework-agnostic SKILL.md files live in skills/. If your Skills CLI supports repository subdirectory sources:

npx skills add basicmachines-co/basic-memory/skills -g

For Claude and ChatGPT, upload basic-memory.zip or basic-memory-chatgpt.zip from the skills-latest release; see skills/README.md.

If your installed Skills CLI cannot load that source, update the CLI or copy the memory-* directories from skills/ into your agent's skills directory.

Hermes keeps its native plugin shape under integrations/hermes:

hermes plugins install basicmachines-co/basic-memory/integrations/hermes

Hermes does not install a plugin's Python dependencies, so also add the mcp package to the Hermes venv — see the plugin README for that step and the supported Hermes releases.

OpenClaw stays package-native and publishes from integrations/openclaw:

openclaw plugins install @basicmemory/openclaw-basic-memory

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

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

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

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

claude mcp add basic-memory -- uvx --prerelease=allow basic-memory mcp

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

[mcp_servers.basic-memory]
command = "uvx"
args = ["--prerelease=allow", "basic-memory", "mcp"]
default_tools_approval_mode = "approve"

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

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

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?"

• 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.
• Optional search reranking. Rescore the strongest vector and hybrid candidates with a local FastEmbed cross-encoder or a LiteLLM-backed provider.
• 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.

Reranking adds a second relevance pass after vector or hybrid retrieval. It is disabled by default because it adds inference latency and, for the local provider, a first-run model download. Text, title, and permalink searches keep their existing ranking.

Enable the default local FastEmbed reranker:

export BASIC_MEMORY_RERANKER_ENABLED=true

The default model is jinaai/jina-reranker-v1-tiny-en. To use a hosted reranker through LiteLLM instead:

export BASIC_MEMORY_RERANKER_ENABLED=true
export BASIC_MEMORY_RERANKER_PROVIDER=litellm
export BASIC_MEMORY_RERANKER_MODEL=cohere/rerank-v3.5
export COHERE_API_KEY=...

The feature fails fast on invalid configuration and does not silently fall back to retrieval order when an enabled provider fails. See the semantic search guide for provider setup, all settings, tuning, pagination, and failure behavior.

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.

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.

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

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

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?

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.

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_notes, recent_activity, list_directory
• Knowledge graph: build_context (navigates memory:// URLs)
• Projects: list_memory_projects, list_workspaces, create_memory_project, delete_project
• Schema: schema_infer, schema_validate, schema_diff
• Compatibility & diagnostics: search, fetch, basic_memory_diagnostics

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

# 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

# Config
basic-memory config list                        # all settings, effective values, env overrides
basic-memory config set cli_output_style plain  # validated through the config model
basic-memory config unset cli_output_style      # revert to default

# 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.

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 }

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.

Basic Memory uses Loguru. Defaults vary by entry point:

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

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

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
just doctor           # File <-> DB consistency check (temp config)
just package-check    # Claude Code, skills, Hermes, OpenClaw package checks
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.

AGPL-3.0.

Built with ♥️ by Basic Machines