Context7
Up-to-date docs for AI agents
作者提供的说明(英文原文)
Cross-machine, file-first memory for Claude Code: markdown + SQLite FTS5, synced with git
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"anamnesis": {
"command": "uvx",
"args": [
"anamnesis-memory",
"serve"
]
}
}
}在终端中运行这条命令
claude mcp add anamnesis -- uvx anamnesis-memory serve粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"anamnesis": {
"command": "uvx",
"args": [
"anamnesis-memory",
"serve"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"anamnesis": {
"type": "stdio",
"command": "uvx",
"args": [
"anamnesis-memory",
"serve"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过 GitHub 账户 oscardvs 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.1.3)于4个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。
同一分类中有:Context7, Codebase Memory, Exa
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
Cross-machine memory for Claude Code
Website · Docs · Benchmark · Dashboard
uv tool install anamnesis-memory && anamnesis init
ἀνάμνησις *(anamnesis)*: Greek for *recollection*, the act of calling knowledge back to mind.
Anamnesis is a local-first, file-based memory layer for Claude Code that syncs across your own machines. What Claude learns about your projects (conventions, architecture decisions, fixes that worked, what you did yesterday) is stored as plain markdown, indexed locally for search, and kept in sync over your private network.
Claude Code's own memory stays on the machine where it was written. Copying a SQLite index through a cloud folder such as Dropbox or iCloud corrupts it. Anamnesis syncs the markdown with git instead and rebuilds the index on each machine, so a note written on your desktop is searchable from your laptop.
No cloud account is required. The memory stays on your machines, version-controlled and human-readable.
┌─────────────┐ git over your private mesh ┌─────────────┐
│ desktop │ ◄──────────── (Tailscale) ────────► │ laptop │ │ │ │ │ │ Claude Code│ │ Claude Code│ │ ▼ │ │ ▼ │ │ MCP server │ markdown (source of truth) │ MCP server │ │ ▼ │ + SQLite FTS index (rebuilt locally) │ ▼ │ │ ~/.anamnesis│ │ ~/.anamnesis│ └─────────────┘ └─────────────┘
~/.anamnesis/memory/, readable and git diff-able. The markdown is the source of truth; everything else is derived from it.anamnesis merge consolidates near-duplicates. Generated notes carry provenance and confidence in their front-matter. merge --apply is gated on your eval set so it does not lower recall, and anamnesis eval measures reflection before and after on a sandbox copy.Prereqs: Claude Code, uv, and git.
uv tool install anamnesis-memory && anamnesis init
anamnesis init registers the MCP server with Claude Code at user scope, installs the SessionStart, SessionEnd, and PreCompact hooks, configures the store at ~/.anamnesis, and runs a first sync. It is idempotent: it backs up settings.json and does not duplicate hooks. --print shows the full plan without writing anything, and --local-only skips the remote until you want one.
Claude Code gets five tools: memory_search, memory_list, and memory_status (read-only, safe to auto-approve), plus memory_write and memory_sync. Full reference: CLI · MCP tools · configuration.
Developing from source instead
git clone https://github.com/oscardvs/anamnesis && cd anamnesis/server
uv venv --python 3.12 uv pip install -e ".[mcp,dev]" uv run anamnesis init --print
The repo also ships a project-scoped .mcp.json. Claude Code launches MCP servers with a filtered environment, so ANAMNESIS_HOME / ANAMNESIS_MACHINE_ID / ANAMNESIS_GIT_REMOTE belong in its "env" block, not your shell. Server internals: server/README.md.
Memory is a git repo (~/.anamnesis/memory/) synced over your private Tailscale mesh, or any git remote you control. Set it up once:
tailscale up). Pick one always-on machine to host the shared repo; tailscale status prints its MagicDNS name (for example host.your-tailnet.ts.net). git init --bare -b main ~/anamnesis-memory.git
anamnesis init --remote 'you@host.your-tailnet.ts.net:anamnesis-memory.git'
The host itself uses the local path: --remote "$HOME/anamnesis-memory.git".
Sync runs commit -> pull --rebase -> push and rebuilds the local index after pulling, so a note written on one machine is searchable on the others within a sync cycle. If you started with --local-only, re-run init --remote ... later; the store attaches to the remote and pushes its history.
anamnesis init installs three Claude Code hooks:
Two more commands build on them:
anamnesis config set reflection.provider ... at an OpenAI-compatible model and anamnesis reflect distills accumulated session notes into durable conventions. With reflection.auto set, it runs at session end once a project has enough unreflected notes. anamnesis merge consolidates near-duplicates and only applies if recall on your eval set holds.anamnesis import copies Claude Code's own per-project memory into the store, so notes you already wrote for it are included.To set the hooks up by hand instead of with init, copy examples/hooks.settings.json into ~/.claude/settings.json and point it at your install.
bench/cross-machine-tokens/ runs one scripted task on a fresh machine twice: once without Anamnesis, where the agent explores the project to learn its conventions, and once with the real SessionStart memory block injected. It drives the Claude Code CLI headlessly on a synthetic project, so a Pro/Max subscription is enough and no API key is needed.
The committed result.json (3 runs per arm on claude-opus-4-8) shows about 8% fewer total input tokens with memory, 366k versus 336k on average, with output tokens and turn count about the same. The conventions were known from the first turn instead of being rediscovered. An earlier version of the scenario used a 5-file project and showed no difference; that null result is documented in the same README.
A web GUI for the memory store: browse and full-text search every note, edit markdown with per-note history, see every machine (which one wrote what and when it last synced), and run reflection from the browser. Provenance badges show where each note came from: you, a session capture, reflection, or import.
npx anamnesis-dashboard # http://localhost:3000
or, from the CLI you already have:
anamnesis dashboard
Needs Node 20 or newer. From a repo clone, cd dashboard && npm run dev works for development.
It is a thin read/write client over the same local store the MCP server uses: it reads the SQLite index directly and shells out to the anamnesis CLI for writes and sync. Use --port, --store, and --no-open to adjust how it serves. See dashboard/README.md for configuration and design notes.
September 2026: v0.1.3 is on PyPI. The local-first core is done and has been used across a real multi-machine setup: the store, the MCP server, the hooks, git sync, the one-command install, the reflection and merge passes with their eval harness, and the dashboard. APIs may still change between releases.
Next: a hosted relay for people without their own mesh (the server already ships anamnesis relay commands behind a [relay] extra, but they are not documented yet) and team memory.
| Path | What |
|---|---|
server/ | The MCP memory server and CLI (Python, FastMCP). |
dashboard/ | The memory GUI (Next.js). |
site/ | The public website and docs (live). |
bench/ | The cross-machine token benchmark and the demo recording pipeline. |
examples/ | A hand-written hooks.settings.json for manual hook setup. |
Issues and discussion are welcome. If the install is rough on your machine, open an issue with the exact command you ran and its output.
Apache License 2.0. See NOTICE.