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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NARA Catalog

作者:ianderso版本 1.1.0i★ –i在你的电脑上运行
注册名称io.github.ianderso/nara-catalog-mcp

安装

概览

作者提供的说明(英文原文)

Genealogical research in the US National Archives Catalog: records, transcriptions, page images.

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: 设计、图片与音频
  • 你需要填写:NARA_API_KEY

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: NARA_API_KEY, NARA_CACHE_DIR, NARA_TIMEOUT, NARA_MONTHLY_CALL_BUDGET

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 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": {
    "nara-catalog": {
      "command": "uvx",
      "args": [
        "nara-catalog-mcp"
      ],
      "env": {
        "NARA_API_KEY": "your-value",
        "NARA_CACHE_DIR": "your-value",
        "NARA_TIMEOUT": "your-value",
        "NARA_MONTHLY_CALL_BUDGET": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add nara-catalog --env NARA_API_KEY=your-value --env NARA_CACHE_DIR=your-value --env NARA_TIMEOUT=your-value --env NARA_MONTHLY_CALL_BUDGET=your-value -- uvx nara-catalog-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": {
    "nara-catalog": {
      "command": "uvx",
      "args": [
        "nara-catalog-mcp"
      ],
      "env": {
        "NARA_API_KEY": "your-value",
        "NARA_CACHE_DIR": "your-value",
        "NARA_TIMEOUT": "your-value",
        "NARA_MONTHLY_CALL_BUDGET": "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": {
    "nara-catalog": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "nara-catalog-mcp"
      ],
      "env": {
        "NARA_API_KEY": "your-value",
        "NARA_CACHE_DIR": "your-value",
        "NARA_TIMEOUT": "your-value",
        "NARA_MONTHLY_CALL_BUDGET": "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

  • NARA_API_KEY 机密 必填 env
    Catalog API key, requested from the National Archives Catalog API team.
  • NARA_CACHE_DIR env
    Directory for the on-disk response cache.
  • NARA_TIMEOUT env
    HTTP timeout in seconds.
  • NARA_MONTHLY_CALL_BUDGET env
    Calls per month the key allows, reported by api_budget.

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8日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 ianderso 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“设计、图片与音频”中的其他服务器比较i

  • 星标数多于此分类中其他 2767 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 2767 个服务器的 46% 更新
  • 基础检查结果等于或优于此分类中其他 2767 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

NARA Catalog 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?

你需要填写:NARA_API_KEY

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(1.1.0)于33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 Python (uv)。

有什么可以替代它?

同一分类中有:Figma Context MCP, Claude Real Video, Figma MCP Server

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

Figma Context MCP

作者:GLips

Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.

在你的电脑上运行★ 16,165MIT5个月前更新
安装

Claude Real Video

作者:HUANGCHIHHUNGLeo

Let any LLM watch a video locally — and search everything it has ever watched.

在你的电脑上运行★ 2,284MIT2个月前更新
安装

Figma MCP Server

作者:figma

The Figma MCP server brings Figma design context directly into your AI workflow.

在云端运行★ 2,15213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。

nara-catalog-mcp

An MCP server for genealogical research in the US National Archives Catalog. Find an ancestor's pension file, service record or census page, read what machines and volunteers have transcribed from it, and fetch the page images you will cite. It also searches NARA's Access to Archival Databases (AAD), which the Catalog cannot reach: the NUMIDENT's Social Security applications and deaths, the WWII Army enlistment cards, and the 1820–1912 ship passenger lists among them.

It works the way a careful genealogist does. A catalogue description is a finding aid, and OCR text, transcriptions and tags are somebody else's reading of the page: all of them are leads. The page image is the source. The tools say which is which, and the server tells the model to read the image before citing it.

Nothing here writes to the Catalog, and nothing here keeps a family tree. The server finds and reads records; what you conclude from them belongs in your genealogy software, or in a family-tree MCP server running alongside this one.

The tools work on any record the Catalog describes, so a historian or a journalist can use them too. The examples throughout are about tracing people.

This is an independent project. It is not affiliated with, endorsed by, or supported by the National Archives and Records Administration.

Tools

The server publishes 21 tools. Twenty only read, and are annotated read-only for the client. One, download_page_image, writes a new file to local disk; it never overwrites one.

Finding a record

ToolPurpose
search_recordsSearch by title or full text. Returns totals plus compact summaries: NAID, hierarchy, holding unit, date coverage, image count. Each series names its creator, the office that made it, which tells apart the many series sharing a title.
search_records_advancedThe same search with the filters that narrow a common name: date range, record group, collection, ancestor NAID, level of description, microfilm publication number, local identifier, any control number, Congress number, reference unit, creator, person or organisation, place, type of materials, recurring date, digitised-only, "has transcriptions/tags/comments", exact matching of identifiers, search_after cursor paging past 10,000 hits, and each hit's OCR text (NARA's and partners') folded in on request.
browse_childrenThe immediate children of a node: record group to series to file unit to item. Walk down from a series you trust.

Reading a record

ToolPurpose
get_recordRead one record in full by NAID: scope and content note, hierarchy, reference units, every page image with its object id.
get_record_imagesPage images in page order, each with its object id and URL — the evidence to read before citing.
download_page_imageSave one page to a new local file, by page number or by the object id an OCR or transcription entry names. The media host is open, so this spends no API quota.
get_online_availabilityWhere else the record is published online, including by commercial partners.
get_partner_digital_objectsDigital object ids a commercial partner (Ancestry among them) has matched to this NAID. An empty list is the common answer.

What machines and other people read in it

Everything in this group is somebody else's reading of the document. It tells you which page to open. It does not tell you what the page says.

ToolPurpose
get_extracted_textOCR text extracted from the page images, per digital object, with who produced it, and the object total and next results page when a file runs longer than one call.
get_transcriptionsCitizen transcriptions — how you get into a handwritten pension file that OCR cannot touch.
get_tagsCitizen tags, which on genealogical records are usually the names of the people inside the file.
get_commentsOther researchers' notes on the record.

Searching the documents rather than the catalogue

ToolPurpose
search_by_contribution_textSearch transcriptions, tags, comments and OCR text — and get full record summaries back.
search_transcriptionsFind records whose transcribed text mentions a name or phrase.
search_tagsFind records carrying a tag, exactly or by word.
search_extracted_textFind records whose partner-contributed extracted text matches.
search_commentsFind records other researchers have commented on.

NARA's Access to Archival Databases (AAD)

AAD serves a selection of NARA's electronic records as searchable tables. Each row is a database entry an agency clerk typed from a record: a transcription or index entry, not the record, and cited as an electronic record. These tools need no key and spend none of the Catalog allowance.

ToolPurpose
aad_list_seriesThe series in an AAD category (genealogy by default), each with its files and their ids. A search runs on one file.
aad_searchSearch one file by free text over the whole row and by named fields; 50 rows a page, each with its record id.
aad_get_recordOne row in full, every coded value with its meaning, and a citation in NARA's recommended form with the date retrieved.

Housekeeping

ToolPurpose
api_budgetLive calls and cache hits this session, the month's live calls from a ledger beside the cache, and what remains of the key's monthly allowance.

Setup

You need Python 3.11 or later, uv, and a Catalog API key. Request a key from the Catalog API team via the API documentation; the default allowance is 10,000 calls per month.

There are two ways to run the server.

Without cloning. uvx fetches it from PyPI and runs it in one step, and caches the result:

NARA_API_KEY=your-key uvx nara-catalog-mcp

From a clone, which is what you want if you will change it:

git clone https://github.com/ianderso/nara-catalog-mcp

cd nara-catalog-mcp uv sync cp .env.example .env # then put your key in it uv run nara-catalog-mcp # stdio server, usually launched by the client

Either way the server speaks MCP over stdio, so you will normally let an MCP client start it rather than run it by hand.

Claude Desktop

Without cloning:

{

"mcpServers": { "nara": { "command": "uvx", "args": ["nara-catalog-mcp"], "env": { "NARA_API_KEY": "your-key" } } } }

From a clone (the env block can be dropped if the key is in the clone's .env):

{

"mcpServers": { "nara": { "command": "uv", "args": ["--directory", "/path/to/nara-catalog-mcp", "run", "nara-catalog-mcp"], "env": { "NARA_API_KEY": "your-key" } } } }

A desktop app does not always inherit your shell's PATH. If the server fails to start because uv or uvx cannot be found, give the full path that which uvx prints as the command.

Claude Code
claude mcp add nara --env NARA_API_KEY=your-key -- uvx nara-catalog-mcp

or, from a clone whose .env holds the key:

claude mcp add nara -- uv --directory /path/to/nara-catalog-mcp run nara-catalog-mcp

Configuration

All settings come from the environment. A .env file in the directory the server starts in supplies any that the environment does not; with uv --directory that is the clone. Only that directory is read — not its parents, and not the directory the package is installed in.

VariableMeaning
NARA_API_KEYYour Catalog API key. Required by the Catalog tools; the AAD tools need none.
NARA_CACHE_DIRResponse cache directory. Default ~/.cache/nara-catalog-mcp.
NARA_TIMEOUTHTTP timeout in seconds. Default 60.
NARA_MONTHLY_CALL_BUDGETCalls per month the key allows, reported by api_budget. Default 10000.

A missing key, or an unusable value, is reported on the first tool call as a not_configured result naming the variable.

The call budget

A Catalog key is capped per month, and a sweep across many names will exhaust it faster than expected. Every successful response is cached on disk, keyed by endpoint and query, so repeating a call costs nothing. Live calls are also written to a ledger, budget.json beside the cache, so api_budget reports the month's spend across sessions as well as this session's live calls and cache hits. A rejected call counts as live, since it reached the API. The ledger sees one machine and one cache directory; the Catalog's own count is the authority.

The cache never expires. Pass refresh=true to get_record, get_record_images, get_extracted_text, get_transcriptions, get_tags or get_comments to re-read one answer from the Catalog: that spends one call and replaces the cached copy. New transcriptions and tags arrive over time, and a file that was paper-only can be digitised, so a cached "nothing here" is the answer most worth refreshing. Deleting NARA_CACHE_DIR still works, and also resets the month's ledger.

Searching past the first 10,000 hits

page stops working beyond 10,000 results, which a common surname passes. search_records_advanced reports a paging_note when you hit that boundary; either narrow the search or re-run it with search_after="*" and follow the next_search_after value from each response.

How a search behaves

title matches words in the record title and is the precise option — case files are usually titled with the person's name. query searches the full description: broader, noisier, and worth reaching for only when a title search finds nothing.

Results come back as summaries rather than whole records. A raw Catalog record is large and mostly irrelevant to the decision you are making, which is whether this record is worth opening.

Searching AAD

AAD has no API, so aad_* read its web pages the way a browser does, and parse them. That shapes how they behave:

  • One file at a time. A big series is split into files, and a search runs on one. The NUMIDENT is split by entry type (application, claim, death) and by surname range, so aad_list_series comes first.
  • Fields by name. fields={"LAST NAME": "PRESLEY", "DATE OF BIRTH (YEAR)": "1930-1935"}. A field AAD stores as a code, such as a state or a country, cannot be searched by name: put its meaning in query, which matches the whole row, code meanings included.
  • Slow on purpose. One request at a time, at least two seconds apart, and a search usually takes two requests because AAD answers first with a "Please Wait" page. Answers are cached for seven days, under NARA_CACHE_DIR/aad; refresh=true on aad_get_record fetches a row again.
  • Record ids are not stable. NARA reloads files, and a reload can renumber the rows. Search again rather than reuse an old id, and cite a row by its fields, its file and its series.
  • A row is not the record. It was keyed from an SS-5, a punch card or a manifest, with the keying errors that brings, and no file holds everyone. The NUMIDENT has entries only for people with a verified death or born before 1908, and its death file omits state-reported deaths. Each answer carries AAD's own notice for the file, and a NUMIDENT answer says what that file leaves out.

Notes

  • A description is not evidence. It summarises a file; it says nothing about what any individual page contains. Read the images before citing.

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