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

ResearchZosho

作者:Wyrdsekai版本 0.7.0i★ –i在你的电脑上运行
注册名称io.github.Wyrdsekai/researchzosho

安装

概览

作者提供的说明(英文原文)

Deep research assistant that checks its citations against the sources and keeps what it found.

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)。
  • 需要你自己填写: RESEARCHZOSHO_LIBRARY

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": {
    "researchzosho": {
      "command": "npx",
      "args": [
        "-y",
        "@wyrdsekai/researchzosho-mcp"
      ],
      "env": {
        "RESEARCHZOSHO_LIBRARY": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add researchzosho --env RESEARCHZOSHO_LIBRARY=your-value -- npx -y @wyrdsekai/researchzosho-mcp

运行前请先填写空着的值。

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": {
    "researchzosho": {
      "command": "npx",
      "args": [
        "-y",
        "@wyrdsekai/researchzosho-mcp"
      ],
      "env": {
        "RESEARCHZOSHO_LIBRARY": "your-value"
      }
    }
  }
}

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": {
    "researchzosho": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@wyrdsekai/researchzosho-mcp"
      ],
      "env": {
        "RESEARCHZOSHO_LIBRARY": "your-value"
      }
    }
  }
}

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。

需要你填写的值

  • RESEARCHZOSHO_LIBRARY env
    The library folder (default ~/researchzosho-library)

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9日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 Wyrdsekai 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 5763 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 5763 个服务器的 100% 更新
  • 基础检查结果等于或优于此分类中其他 5763 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

ResearchZosho 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(0.7.0)于今天进入注册中心。

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, Docker。

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:↓ 每周下载量i★ 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

Up-to-date docs for AI agents

作者:upstash广泛使用↓ 97.3万/周★ 6.4万3天前更新

电脑或云端

Codebase Memory

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

作者:DeusData广泛使用↓ 1.8万/周★ 4.8万23天前更新

在你的电脑上运行

Exa

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

作者:exa-labs广泛使用★ 52132个月前更新

在云端运行✓ exa.ai

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。

ResearchZosho

研究蔵書, *the research holdings.* The Research Harness For The Rest Of Us.

ResearchZosho is an open-source deep research assistant. Give it a question and it searches the web and scholarly papers, or only your own PDFs, and writes a report in which every claim points at a source. It runs on your own computer with a local LLM (llama.cpp, Ollama, LM Studio) or a hosted API.

Three people, one problem.

Your vet mentions a new drug for your dog's cancer. The follow-up is in three days. You want to know what the studies say: how well it works, for which breeds, and what the side effects are. The answer is spread across twenty papers, a regulator's review, and many pages that only look like medical advice.

You are tracing your family. Your great-grandfather is in the 1911 census in Osaka. By 1921 he is gone from every record the family knows about. Somewhere there are ship manifests, a prefecture's emigration lists, and an old newspaper notice. Most of them are in Japanese. None of them are on the first page of a search.

You are writing one chapter of a thesis on the influence of the Soviet-Afghan War on 1990s British science fiction. You have forty papers and articles saved, in three languages. You have one week to work out what they agree on, where they disagree, and what nobody has looked at yet.

None of that can be read in one evening. That is the job ResearchZosho does. You give it the question. It reads and notes each fact with the source it came from. When it is done, a write-up is waiting: what it found, where the sources disagree, and what it could not resolve. Every claim in it points at a source you can check. It keeps what it found, so the next question on the same subject does not start from zero. If a paper you used gets a new version, or two of your own findings contradict each other, it tells you.

Nothing counts as valid until you have reviewed it.

It runs on your own computer with a model you pick, local or hosted. It is free and open source. It is for anyone who needs reliable research done.

This is The Research Harness For The Rest Of Us.

→ [LIBRARIAN_HOWTOUSE.md](docs/LIBRARIAN_HOWTOUSE.md): how to use it day to day → [LIBRARY_PROTOCOL.md](docs/LIBRARY_PROTOCOL.md): for programmers, how a program talks to it → [FAMILY_HISTORY.md](docs/FAMILY_HISTORY.md): researching your family, from a relative's notes to records and a family tree → [YOUTUBE.md](docs/YOUTUBE.md): researching what is on YouTube — channels, what is said in a video and when, channels like one you know — without an API key

→ [BEDROCK.md](docs/BEDROCK.md): using the models in your own AWS account (Amazon Bedrock) with your own AWS sign-in

→ [MODELS.md](docs/MODELS.md): which model to run, from what we measured: the local models by your graphics card's VRAM first, then the hosted ones by what they got right, how long a run took and what it cost


What you can do with it

Send it a question. It works out what needs answering. It reads in parallel: the web, and the scholarly literature by DOI through Crossref and OpenAlex, and when the question calls for them the web archives, the Internet Archive, digitised historical newspapers, the National Diet Library's digitised Japanese books, the archives of source code and the video sites beside YouTube. A page that is gone is read from its archived copy. It writes the answer up in sections. It keeps going until the job is done, or for as long as you allow. It also reads sources in other languages, especially when the question points at a non-English language. The write-up says which languages its sources were in.

Check the answer. Every write-up ends with a table of the facts it used. Each fact has its source and a quote. A numbered list of unique sources follows. Before the write-up is shelved, each sentence that cites a source is checked against that source. A problem is called out. If it cannot read a source, because of a paywall, a login or another issue, it lists that source so you can supply the text yourself.

Keep bad sources out. A claim with one source stays a draft until a second, independent source backs it. A retracted paper disputes the claims that cite it. A site you ban is not used. A site you trust counts as a primary source.

Decide what stands. Each claim starts as a draft. You accept it, dispute it or retire it. The library uses what you accept next time.

Talk to it. researchzosho chat is a conversation with the Librarian. Ask what the shelves hold, ask a follow-up, say "find out …" to start a research run, ask "how did that go?", or go through the inbox. Every reply cites a look-up you can open. A figure it cannot back is marked as its guess. The same conversation is on the pages at /chat.

Ask what you already know. researchzosho ask "…" shows what the library has on a question: each claim, where it came from, and whether it is accepted or still in dispute.

Bring your own documents. A PDF, a web page, or a whole folder. Point it at a folder and every document in it is shelved as a collection. Then ask a question that searches only those documents, or one that starts there and goes to the web afterwards for more.

Get book recommendations. Ask for a book to read first on a subject, what a book covers, or what to read next. The recommendations come from the library catalogues (Open Library, Japan's National Diet Library and others), never from the model's memory, so every book named is a real one with a link to its record. It looks past the bestseller lists and says what each book covers and who it is for.

Use your own shelf. Point it at your Calibre library and it learns what you go for: the subjects, the authors you come back to, the decades and languages. researchzosho myshelf like " " recommends books on your shelf like one by what the texts say, not by who wrote them. A nightly reading of your books builds a card for each, which describes the book and nothing about you. Say which rows you liked and disliked, and the next lists move.

Know what you own. Import your purchase records (the zip Amazon sends you, a mailbox of order confirmations, a card statement) and the library can tell what you already have. Every night it checks the open product-safety feeds against them, and a recall that may concern you waits in the inbox.

Research a purchase. Ask what to buy and the run looks only at what shops list right now in your country, with the price, the datasheet, recall notices, repairability and what owners say. The table judges fit against your need, not popularity. For used, vintage or out-of-print things it asks eBay and gives you ready search links for the marketplaces no program may read.

Ask how to do or make something. A craft, a hobby, a sport, a martial art or a trade. The answer comes with the kit: every material and tool, what it is for, what stands in for it, and where to get it. For a sport or a martial art, the gear in the order you need it and where to learn. For a community you want to join, such as the SCA or a reenactment society, how to join and what its rules ask of your equipment.

Podcasts and videos. A question about a podcast, a host or an episode reads what was said, with the time it was said, and cites the episode. Follow a show and its new episodes are noted as they arrive. A question about videos searches YouTube and the sites beside it and cites the moment.

Ongoing research, every night. Every night it runs the searches you have declared ongoing. It looks into questions it could not answer before. It re-reads a few accepted claims against their sources. It notices new versions of papers you cite. It keeps a dated backup. On Sundays it leaves you two lists: claims that look like duplicates, and documents you might clean out. It never merges, deletes or decides for you.

See how things connect. When a claim says a person lived in a place, or an author wrote a work, the library keeps the connection. researchzosho map "Arthur Ellis" shows everything around a name. The service draws it in your browser. This connects the research you have built up.

Open it in a browser. The service has basic pages: search, ask, read a claim with its sources, walk the subjects, see what changed and what is running, send a question, and download any write-up as Markdown or PDF. For a desktop editor, researchzosho vault writes a folder that Obsidian, SoloMD or SilverBullet can import.

Let other programs use it. Claude Code, Codex, Gemini CLI and any other MCP host can ask the library directly. A small HTTP service with Python and Java clients covers everything else.

Reach it from outside your home. researchzosho share makes the library reachable now, behind an encrypted relay (a Cloudflare quick tunnel at first, Tailscale Funnel for an address that lasts), free, with no port opened at home: anyone with the link sees the sign-in page, and only a person you invited gets in, with their name and password, a passkey, or a one-time code as a second step. Invite a person with one link; they choose their password when they open it.

Sign in simply. No tokens to paste. You make your account once, with a name and a password, and sign in from any phone or computer. On the library's own computer your browser needs no sign-in. Add a passkey, so your fingerprint or face signs you in, or a one-time code from an authenticator app as a second step. Programs still use tokens.

Getting started

Research runs need a model server that speaks the OpenAI chat API. That can be a local one (llama.cpp, Ollama, LM Studio) or a hosted API with a key (OpenAI, DeepSeek, Gemini, OpenRouter and others). You also need Java 21 or newer, unless you take a build that carries its own runtime. The installer picks that build for you when Java is missing.

Research runs also need a web search backend. It matters as much as the model. Use a Brave Search API key (free plan), or SearXNG (setup starts one with Docker). With neither, the built-in fallback searches Wikipedia and the scholarly literature only. Asking what the library already has works without a model.

git clone https://github.com/Wyrdsekai/researchzosho.git

cd researchzosho bin/researchzosho setup

When it is done, open http://127.0.0.1:4649/ in a browser.

setup asks a few questions. Each has an answer already filled in:

  • where the library installs
  • which model it uses, and which it checks for
  • which web search backend
  • whether search is by meaning, by keyword, or both
  • whether to run it as a service
  • which programs to connect

Then it shelves a document you name and answers a question about it. Run it again any time to change one thing. --yes takes every default.

The release installs on Linux, macOS and Windows. If you already use CodeZaiku, codezaiku install researchzosho fetches the release, checks it, and runs setup.

Settings live in ~/.researchzosho/config as key = value lines, or in the environment. These are the ones you are most likely to change:

settingwhat it is
RESEARCHZOSHO_DRIVEthe model server, for example http://localhost:8080 or https://api.openai.com/v1
RESEARCHZOSHO_MODELthe model name to ask for
RESEARCHZOSHO_JUDGE_DRIVE / RESEARCHZOSHO_JUDGE_MODELa second, stronger model for the judgment steps (planning, the critic, the write-up, the citation check), while a local model does the reading
RESEARCHZOSHO_EMBEDan embeddings server (OpenAI embeddings call), so search works by meaning as well as by words; off for words only. researchzosho embed start runs one with Docker (Text Embeddings Inference, about nine times faster than llama.cpp on the same model)

| `RESEARCHZOSHO_LIBRA

只显示了开头部分;其余内容请在仓库中阅读

问 PopNx