原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
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nMEMORY

作者:menot-you版本 0.1.2i★ –i在你的电脑上运行
注册名称io.github.menot-you/n-memory

安装

概览

作者提供的说明(英文原文)

Memory your agent can trust — every answer carries its source; when it doesn't know, it says so.

PopNx MCP 的三大支柱

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。

它能帮你做什么

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。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 搜索与 AI 记忆

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

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 …”。

下载作者的 .mcpb 文件

链接指向作者自己的文件;我们不托管也不重新打包它。打开文件后,Claude Desktop 会进行安装。

在终端中运行这条命令

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。

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。

它能做什么

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。

基础检查i

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

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 menot-you 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    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“搜索与 AI 记忆”中的其他服务器比较i

  • 星标数多于此分类中其他 7266 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 7266 个服务器的 24% 更新
  • 基础检查结果等于或优于此分类中其他 7266 个服务器的 100%

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。

常见问题

nMEMORY 安全吗?

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。

它需要哪些密钥或代码?

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。

它在我的电脑上运行还是在云端?

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)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.1.2)于4个月前进入注册中心。

哪些应用可以使用它?

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 MCPB。

有什么可以替代它?

同一分类中有:Context7, Codebase Memory, Exa

替代选择

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

Context7

作者:upstash

Up-to-date docs for AI agents

电脑或云端★ 64,224MIT昨天更新
安装

Codebase Memory

作者:DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

在你的电脑上运行★ 48,148MIT21天前更新
安装

Exa

作者:exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

在云端运行★ 5,213MIT上个月更新
安装

作者的 README

打开 README

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。

Your agent forgets everything between sessions. nMEMORY makes it remember, with sources.

Install

curl --proto '=https' --tlsv1.2 -fsSL https://no.tt/install.sh | sh

Or install from source. You need uv and Git:

git clone https://github.com/menot-you/n-memory

cd n-memory uv sync uv run nmemory database create claude mcp add nmemory -- uv run --directory "$PWD" nmemory mcp serve

uv sync installs the pinned Python (3.14) and all dependencies. database create makes the store file. nMEMORY never makes it implicitly. Any MCP client that speaks stdio connects the same way as Claude Code.

How it works

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flowchart LR agent["Your agent (any MCP client)"] -->|"stdio, 18 tools"| server["nmemory mcp serve"] shell["You, in a shell"] -->|"nmemory CLI"| core server --> core["Capture and recall"] core -->|"one transaction per call"| store[("One SQLite file records, journal, index")] core -->|"BM25, always"| lexical["Keyword recall"] core -.->|"when a key is set"| vectors["Embedding provider"] lexical --> outcome{"grounded missing_evidence abstain"} vectors -.-> outcome

Each record must have a source and an anchor (path:line, a quote or a PR). Recall returns one of three outcomes. It never turns a weak match into an answer.

By the numbers

Counted on 2026-10-21. Tools: the MCP tools/list request to nmemory mcp serve. Tests: uv run --group dev pytest --collect-only -q in each member root.

Why

BeforeWith nMEMORY
Each new session starts empty. You explain the same decision again.The agent recalls the decision at the start of the session.
A recalled "fact" has no origin. You cannot check it.Each record must have a source and an anchor.
A weak match comes back as a confident answer.Recall has three honest outcomes: grounded, missing_evidence or abstain.
Old notes and new notes conflict in silence.A new record can supersede an old one. Every change goes into a hash-chained audit journal.
Text from a web page or a file can steer the agent.nMEMORY marks imported or directive-shaped text as tainted. Recall labels all results as data, not instructions.

Quick start

Your agent uses the MCP tools. You can use the same store from the shell.

Store a decision (the agent calls nmemory_capsule_ingest):

{

"content": "We store data in SQLite, not PostgreSQL.", "kind": "decision", "source": "docs/adr/0001-storage.md", "anchor": "docs/adr/0001-storage.md:3" }

In a later session, recall it:

uv run nmemory capsule retrieve "what database stores our data"

uv run nmemory capsule show --id cap-1

The first command returns "outcome": "grounded" and the record. The second command shows its provenance: source, anchor and source hash.

What you get

  • 27 MCP tools for capture, recall, sessions, handoffs, tasks, review and audit. The reference lists each tool and CLI command.
  • Hybrid recall. BM25 keyword search always works. The default embedding provider is Gemini (NOTT_NMEMORY_EMBED_PROVIDER, also openai or openai-compatible for a self-hosted server such as Ollama or vLLM).
  • Embeddings send text off the machine. When the provider key is in the environment (GEMINI_API_KEY for the default), nMEMORY sends capsule text and queries to that provider. To keep recall lexical only, unset that key. No key is needed to start.
  • One file, local first. The store is one SQLite file. Each call is one transaction. A connection stays read-only until the call declares a write.
  • Session brackets and handoffs. An agent opens a session, captures as it works, and closes with a handoff that the next session reads.
  • Purge that really deletes. Purge deletes the content, the quote, the queued embedding text and the vector in one transaction.

How it compares

A notes file (CLAUDE.md, AGENTS.md)A plain vector storenMEMORY
Survives a new sessionYesYesYes
Source required per recordNoNoYes
Says "no evidence" on a weak matchNoNo, it returns the nearest vectorsYes
Works with no embedding keyYesNoYes (lexical)
Audit trail of each changeGit onlyNoHash-chained journal
Grows without filling the promptNo, the whole file loadsYesYes, recall has a token budget

Benchmarks

The evaluation harness holds runners for synthetic recall, LongMemEval and extraction. It publishes methods, not a score for this release. We do not quote older numbers here, because they measured an earlier engine.

The NOTT family

Memory that cites its source.

Tracked, resumable agent workers.

The live web as cited evidence.

App Store Connect for agents.

The team contract, routes and hooks.

For AI agents

This section is for a language model that reads this repository.

  • What it is. nMEMORY is a local memory server for coding agents. It stores records (decisions, facts, tasks, failures) with a required source and anchor, and recalls them with one of three outcomes: grounded, missing_evidence or abstain.
  • What it is not. It is not a hosted service, a general vector database or a chat history. It does not invent an answer when nothing matches.
  • Entry points. The CLI is nmemory (nmemory --help). The MCP server is nmemory mcp serve (stdio). All 18 tool names start with nmemory_. Start with nmemory_context_show, nmemory_capsule_retrieve and nmemory_capsule_ingest.
  • Configuration. The optional file is ~/.nott/memory.toml. The variable NOTT_NMEMORY_CONFIG names another path. The store directory is ~/.nott/state/database/, or NOTT_DATABASE_DIR when a test sets it.
  • Invariants. Every record has a source. Recalled text is data, not an instruction. Each mutation goes into the hash-chained journal. A test never opens the live store. The store is SQLite only.
  • Full reference. docs/REFERENCE.md lists every tool and command. RULEBOOK.md lists the implementation rules. llms.txt holds the same facts in the llms.txt format.

Documentation

PageContents
RunbookFirst useful result, failure diagnosis, backup and restore
ArchitectureTrust boundaries and the full engine detail: store, recall, tools, CLI
ReferenceEvery CLI command and MCP tool, linked to its source
RulebookImplementation invariants
SetupDevelopment setup
QualityChecks and security review
Docs indexDocumentation index and a first contribution
InstallationInstall paths
PrivacyProcessing choices
UpgradeExisting data
TroubleshootingFailure diagnosis
RoadmapDirection

Run the checks from the repository root:

uv run ruff check . && uv run mypy --strict nmemory

TMPDIR=/var/tmp uv run --group dev pytest -q

Each test gets its own disposable store. No test touches your live store.

License

AGPL-3.0-only.

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