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。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Vulcanus

作者:sunsatosolutions版本 0.6.3i★ –i在你的电脑上运行
注册名称io.github.sunsatosolutions/vulcanus

安装

概览

作者提供的说明(英文原文)

A validated Markdown memory vault your coding agent can recall, project by project.

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: 开发者工具

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。

你需要

  • npm已安装 Node.js(用于 npx 命令)

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": {
    "vulcanus": {
      "command": "npx",
      "args": [
        "-y",
        "@sunsato/vulcanus",
        "serve"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add vulcanus -- npx -y @sunsato/vulcanus serve

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "vulcanus": {
      "command": "npx",
      "args": [
        "-y",
        "@sunsato/vulcanus",
        "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。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "vulcanus": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@sunsato/vulcanus",
        "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 sunsatosolutions 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“开发者工具”中的其他服务器比较i

  • 星标数多于此分类中其他 4906 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 4906 个服务器的 62% 更新
  • 基础检查结果等于或优于此分类中其他 4906 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

Vulcanus 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(0.6.3)于24天前进入注册中心。

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 Node.js。

有什么可以替代它?

同一分类中有:GitHub, Desktop Commander, Cloudflare MCP

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

GitHub

作者:github

Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.

电脑或云端★ 34,245MIT4天前更新
安装

Desktop Commander

作者:wonderwhy-er

MCP server for terminal commands, file operations, and process management

在你的电脑上运行★ 10,225MIT16天前更新
安装

Cloudflare MCP

作者:cloudflare

Cloudflare MCP servers

在云端运行★ 4,446Apache-2.014个月前更新
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。

Vulcanus

Your coding agent starts every session cold. You re-explain the architecture, repeat decisions you already made, and watch it break a rule you set last week. The context lives in your head and in a scrollback buffer that is already gone.

Vulcanus fixes that at the source. It builds an AI-readable second brain — a Git-versioned vault of linked Markdown that you and your agents both read — and serves it over MCP, so an agent can recall a project instead of guessing at it.

npm install -g @sunsato/vulcanus

vulcanus

Install it globally: the MCP server (vulcanus serve), the skills, and the commit hook all run the vulcanus command, so it has to be on your PATH. npx @sunsato/vulcanus works for a one-off look, but nothing you wire to your agents can reach it.

You answer a few questions, and Vulcanus writes the whole vault — routing layer, operator profile, agent protocol, and one memory cluster per project — then validates that the graph actually holds together. Already keep an Obsidian vault? It adds the memory structure to that vault instead of creating a separate one.

Requires Node 22.12 or newer. It runs locally: no account, and no automatic network call beyond an optional once-a-day version check. Upgrade with npm install -g @sunsato/vulcanus@latest.

A Sunsato product · vulcanus.sunsato.com

Why a vault and not a prompt

A CLAUDE.md that grows forever is the thing this replaces. It gets read in full on every task, it drifts out of date silently, and nothing checks that what it claims is still true.

A vault is layered instead, so recall is scoped: an agent reads the Recall Map, then the one Capsule its task needs, and goes deeper only for authority or detail. vulcanus stats measures that on your own vault — in the demo above, a task-scoped recall reads 59% less than the whole vault. vulcanus doctor then enforces that every link resolves and every project is reachable, so the memory fails loudly instead of rotting quietly.

Wire it to your agent

The vault is only worth as much as the recall it gives your tools, so that is one command each:

claude mcp add vulcanus -- vulcanus serve   # Claude Code, or any MCP client
vulcanus skills --install   # skills that run the real commands, in every repo
vulcanus agents             # the block to paste into a tool's global instructions

MCP server, Skills, and Making agents actually use it below cover what each one exposes.

What it creates

YourVault

├─ AGENTS.md # the protocol AI agents must follow in this repo ├─ CLAUDE.md # points Claude Code at that protocol ├─ USING-WITH-AI.md # how to make every tool recall this vault ├─ README.md ├─ vulcanus.json # the manifest everything is derived and validated from ├─ .claude/skills/ # invocable skills for Claude Code ├─ .agents/skills/ # the same skills for Codex, Cursor, and Gemini CLI ├─ 00_System/ # Index, Recall Map, Admin Profile, Rules, Update Format … ├─ 02_Projects/ # one cluster per project └─ _imports/ # raw AI exports, ignored by Git

Each project cluster is five notes plus any specialized ones you ask for:

NoteHolds
Capsulethe compressed must-remember summary an agent reads first
Hubnavigation and cluster boundary
Contextidentity, definitions, scope
Decisionsconfirmed choices and corrections
Rulesconstraints on future behavior
Architecture / Flow / Visual Direction / Content Guidelinesoptional domain depth

The point of the layering is token economy: an agent reads the Recall Map, then one Capsule, and only goes deeper when the task actually needs authority or detail.

What a project is, and who may hear about it

Two optional fields on each project in vulcanus.json carry what a note cannot enforce:

FieldValuesAnswers
kindumbrella, product, lab, service-brand, client, client-productwhat this project *is*, so an agent knows how to place and summarize it
visibilitypublic, privatewhether an agent may name this project outside the vault

init and add project ask for both, and visibility is recorded either way — "nobody has said" and "the operator said public" are different states, and only one of them is safe to act on. recall returns the marker and, for a private project, an instruction not to name it in anything public. doctor warns on a value it does not recognize rather than failing the vault, because a typo like privte would otherwise read as public to every agent.

This is a signal, not access control: nothing here encrypts or hides a file.

Notes you keep yourself

The generated system layer is a fixed list, so a note you write under the system directory would otherwise read as unmanaged, and the System Hub linking it would read as over-linked — two findings for doing nothing wrong. systemNotes in vulcanus.json names those notes:

{ "systemNotes": ["Release Notes", "Semantic Index Strategy"] }

They are branded like every other system note, so Release Notes resolves to Release Notes in a branded vault. Declaring one only makes the vault aware of it: the note is never created, never rewritten, and update leaves it alone. The System Hub may link it, sync adds the bullet if it is missing, and a note declared but never written is reported so the declaration cannot quietly point at nothing. A system note nobody declared is still reported as unmanaged.

The first question is import

Before anything else, Vulcanus offers to read an existing AI history and propose your project tree from it:

SourceWhat it reads
ChatGPT data exportconversations-000.json … split batches
Claude.ai data exportconversations.json + projects.json
Claude Code~/.claude/projects/**/*.jsonl
Codex~/.codex/**/rollout-*.jsonl
Gemini CLI~/.gemini/tmp/**/logs.json and saved checkpoint- .json chats
Cursorper-workspace chat history (state.vscdb), read through the built-in node:sqlite
Markdown folderany directory of notes — the folder names become the project signal

Locations are auto-detected, so usually you just pick one from a list. A Markdown folder is the exception: it is never probed on its own, and only scanned when you name the path.

Re-running import on the same source proposes only what is new — conversation ids already read are remembered in the vault's state directory. --all re-reads everything. --json prints the candidates with their evidence and writes nothing.

Nothing from your history is copied into the vault unless you accept it. Conversations are read locally, reduced to candidate project names with evidence counts, and discarded. Only the names you tick become notes; the Import Log records how many conversations were scanned, never their content.

Names the source itself grouped conversations under — a Claude project, a repository directory — are the strong signal and come pre-checked. Names inferred purely from title frequency are proposals and start unchecked.

Decisions you already made

Your history usually holds more than project names: the choices you settled and the rules you kept repeating. After the project step, import asks whether to look for them (--memory says yes up front, --no-memory skips the question, and --memory-only skips project discovery for a vault that already has its projects).

  • Only your own messages are read. An assistant's sentence is not your decision.
  • Sentences are matched against decision and rule phrases in English, Turkish, German, and Spanish — "we decided", "from now on", "karar verdik", "ab sofort", "a partir de ahora" — and ranked by how strong the phrase is, how many conversations repeat it, and how recent it is. Questions and code are ignored.
  • A conversation counts toward a project when its source grouped it there or its title names the project. Body mentions do not.
  • What the vault already records is dropped. A candidate that looks like a revision of a live decision is offered as its replacement, so the old one is marked rather than contradicted (see When a decision changes).
  • You review each candidate: accept as decision, accept as replacement, accept as rule, edit the wording, skip, or stop. At most 15 per project per run. Nothing is accepted unattended — --json with --memory-only reports counts only.
  • What you accept is written in the wording you accepted, with a source:: import · · line. Skipped candidates are discarded, and reviewed conversations are remembered so they are not proposed again (separately from project discovery, so one never hides conversations from the other).

--ai-extract [cli] hands the candidate sentences — not transcripts — to an installed AI CLI to merge duplicates, drop noise, and tighten wording, after showing you what will be sent. Anything it returns that does not trace back to a sentence it was given is discarded.

Commands

vulcanus init            # create a vault, or add memory to an existing Obsidian vault (default command)
vulcanus status          # one-screen vault health: projects, notes, doctor result, git state
vulcanus stats           # token budget: what a cold-start agent reads, what recall saves
vulcanus doctor          # validate the vault against its manifest
vulcanus add project     # add projects and wire them into the graph
vulcanus project remove "Name"        # unlink a project; its notes move to _archive/

vulcanus project rename "Old" "New" # folder, notes, and every link, in one move vulcanus project archive "Name" # mark it archived (--restore undoes it)

vulcanus import          # propose more projects from an AI export or a notes folder
vulcanus serve           # serve the vault to MCP clients: recall, search, append_decision, …
vulcanus agents          # print the block that makes your AI tools use the vault
vulcanus skills          # agent skills that run these commands for you
vulcanus update          # bring the vault up to date with a newer CLI
vulcanus sync "topic"    # validate, then commit and push

vulcanus sync --watch # regenerate and revalidate on every edit; never commits

vulcanus hooks install   # a pre-commit hook that refuses to commit a broken graph
vulcanus completion zsh  # completion script for bash | zsh | fish | pwsh

init accepts --lang en|tr|de|es, --ai [cli], and a target directory; add project and import accept --ai [cli]; status and stats accept --json; doctor accepts --repair and --json; import accepts --source, --path, --ai-group [cli], --memory, --no-memory, --memory-only, --ai-extract [cli], --json, and --all; update accepts --dry-run, --force, --profile core|full, and --json; sync accepts --dry-run, --json, and --watch; skills accepts --raw, --install, and --force.

--verbose and --quiet work on every command, and --json implies quiet so machine-readable output owns stdout.

Exit codes are part of the contract: 0 the command did what it said, 1 the vault or the operation failed validation, 2 the command was used wrongly (no vault, bad flag), 130 cancelled at a prompt. Every failure prints what happened, why, and what to do next.

Scripting `

只显示了开头部分;其余内容请在仓库中阅读

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