
Basic Memory
io.github.basicmachines-co由 GitHub 账号 basicmachines-co 发布v1.0.0更新于 Oct 30, 2026
Local-first knowledge management with bi-directional LLM sync via Markdown files.
发布方自己的服务:Memory.fit
概览
本地优先的知识库,把笔记存为 Markdown 文件,AI 助手可读写、搜索并将它们连成知识图谱。
- 可以做什么
- 创建、读取、编辑、移动和删除项目中的 Markdown 笔记
- 按关键词、语义或混合排序搜索笔记,并列出或查找实体
- 沿观察与 wikilink 构成的知识图谱检索上下文
- 管理项目,并校验、推断或比对知识库结构
- 导入已有的 Claude、ChatGPT 或 memory JSON 对话
- 适用场景
- 适合希望助手跨会话记住工作内容、并把这份记忆保存为可用 Obsidian 或编辑器打开的纯 Markdown 文件的场景。也适合需要把个人或项目知识库留在本机而非托管服务的用户。
- 运行要求
- 本地安装需要 Python 与 uv,通过 uvx 加预发布参数运行。笔记默认存放在用户主目录下的 basic-memory 文件夹。可选的云端模式和重排序需要账号或 API 密钥(如 COHERE_API_KEY);可用 BASIC_MEMORY_NO_PROMOS 关闭遥测。
安装
在 SourceWeft 中
- 打开 控制台中的 Basic Memory,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
README
[License: AGPL v3] [PyPI version] [Python 3.12+] [Tests] [Ruff] [图片] [图片] [Ask DeepWiki]
Skip the install — try Basic Memory in the cloud
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.
Basic Memory Teams is now available!
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.
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, 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.
Get started
Pick the path that fits you. Both run the same product on the same Markdown.
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.
Pricing
$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
BMFOSSfor another 20% off for 3 months (~$11.40/mo).
Cloud vs. local
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
Official agent packages
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:
Package-local justfiles are also available when working inside one host:
Claude Code plugin
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:
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.
Shared skills
Framework-agnostic SKILL.md files live in skills/. If your
Skills CLI supports repository subdirectory sources:
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
Hermes keeps its native plugin shape under 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
OpenClaw stays package-native and publishes from
integrations/openclaw:
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:
Restart Claude Desktop. Notes live in ~/basic-memory by default.
Claude Code, Codex CLI, Cursor, VS Code, ChatGPT, Obsidian
Claude Code
For the full memory bridge — session briefings, pre-compaction checkpoints, and
the /basic-memory:* commands — also install the Claude Code
plugin on top of this.
Codex CLI
Add to ~/.codex/config.toml:
Codex can keep its default MCP approval behavior, or you can pre-approve eligible Basic Memory tools by adding this server-scoped setting to the same table:
This does not disable Codex approvals globally or expand which Basic Memory projects the server can access. Codex still requires approval for tools that advertise a destructive annotation, including Basic Memory's writes, edits, and deletes. If you installed the Basic Memory Codex plugin, use its plugin-scoped configuration instead.
Cursor
Add to .cursor/mcp.json (project) or ~/.cursor/mcp.json (global):
VS Code
Add to your User Settings (JSON):
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:
What's New
- Automatic updates. Basic Memory keeps itself up to date for
uv tooland Homebrew installs;bm updatetriggers 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
bm_schema(command="infer"),bm_schema(command="validate"), andbm_schema(command="diff"). - Per-project cloud routing. Route individual projects through the cloud
while others stay local, via API key (
bm project set-cloud). - Explicit note changes.
bm_editupdates existing notes;bm_writecreates notes and 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.
--jsonoutput for scripting, workspace-aware commands, and an htop-inspired project dashboard.
Full CHANGELOG for v0.18 → v0.20.
Optional cross-encoder reranking
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:
The default model is jinaai/jina-reranker-v1-tiny-en. To use a hosted
reranker through LiteLLM instead, first install the optional LiteLLM
SDK, then configure it:
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.
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:
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
Observations
Facts about the entity. Categories in [brackets], tags with #, optional
context in parens.
Relations
Wiki-style links that form the graph. Single-token relation types, or quote multi-word ones.
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:
bm_write,bm_read,bm_edit,bm_move,bm_delete - Search & discovery:
bm_search,bm_list,bm_find - Knowledge graph:
bm_context - Projects:
bm_project(command="list" | "create" | "recent");bm_project_deleteis separate and requires server opt-in. - Schema:
bm_schema(command="validate" | "infer" | "diff") - Manual:
bm_man - Cloud connector adapters:
searchandfetchare registered by Cloud only. Local diagnostics usebm doctor.
Most tools default to text; bm_context defaults to JSON. Pass
output_format="json" for structured responses. Project-scoped tools accept a
name, workspace/project, or external UUID through project.
Use bm_man(page="bm-search(3)") for the installed contract, or see the
tool guide. CLI commands retain their shell names.
CLI essentials
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) orbm update --check(check only)
Disable in ~/.basic-memory/config.json:
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:
This disables promos and all telemetry.
Logging
Basic Memory uses Loguru. Defaults vary by entry point:
Log file: ~/.basic-memory/basic-memory.log (10MB rotation, 10 days
retention).
Environment variables
Development
Basic Memory supports SQLite (default, fast, no Docker) and Postgres (via testcontainers — Docker required).
Tests use pytest markers: windows, benchmark, smoke. See
justfile for the full list.
Contributions welcome — see CONTRIBUTING.md.
License
Built with ♥️ by Basic Machines
来源:README.md,提交 c9bd187
工具
0版本历史
3- v1.0.0最新Oct 30, 2026
- v0.24.1Oct 23, 2026
- v0.23.2Sep 16, 2026
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