NobodyNamed

io.github.michaelcolenso由 GitHub 帳號 michaelcolenso 發布v1.0.0更新於 Oct 24, 2026

US baby name popularity data from SSA records (1880-2025): search, trends, geography, culture.

已驗證Streamable HTTP可網頁執行知識與記憶資料與分析

概覽

AI 產生的概覽

一個以美國社會安全局 1880 至 2025 年嬰兒姓名紀錄為基礎的遠端 MCP 伺服器,讓助理搜尋姓名並檢視趨勢、地理分布與文化背景。

可以做什麼
依前綴搜尋姓名,並取得某個姓名男女兩性的完整年度出生數時間序列,包含趨勢分類、高峰年份與高峰數量。依年份或年代瀏覽熱門姓名、年度排名升降榜,以及依上升、穩定、瀕危、絕跡等趨勢狀態篩選的姓名。並排比較兩到三個姓名,並找出流行軌跡最相似的姓名。檢視地理與文化資訊:各州隨時間的擴散情況、從未採用該姓名的州,以及含估算在世人口、年齡中位數與文化催化因素的預先計算檔案。列出某年首次出現在紀錄中的姓名,並讀取每年前十姓名、涵蓋年份範圍等網站中繼資料。
適用情境
適合想判斷某個姓名是在上升、穩定還是走向消失,比較多個姓名,或了解命名歷史、地區採用情況以及姓名流行背後的文化因素時使用。
執行需求
透過 streamable HTTP 連線至 nobodynamed.com 的遠端端點;未宣告需要身分驗證、環境變數或請求標頭。無須在本機安裝任何內容。
安裝前請注意
僅對公開的 SSA 衍生資料做唯讀查詢,不涉及憑證、付款或寫入操作。估算在世人口、年齡中位數與文化催化因素等為預先計算的估計值,並非官方統計。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 NobodyNamed,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/io.github.michaelcolenso%2Fnobodynamed/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "nobodynamed": {
      "type": "http",
      "url": "https://nobodynamed.com/mcp"
    }
  }
}

README

nobodynamed

Is your name going extinct? nobodynamed shows the popularity, trajectory, and vital status of any American name since 1880, based on Social Security Administration data.

Stack

LayerService
Frontend + APICloudflare Pages + Pages Functions
DatabaseCloudflare D1 (SQLite)
Annual data refreshCloudflare Worker (Cron Trigger + Queues)
Archive storageCloudflare R2

Repository layout

apps/  web/             Cloudflare Pages: static HTML/CSS/JS + Functions    public/        Served as static assets    functions/     Pages Functions (API routes + SSR /name/:name)  ingest-worker/   Cron-triggered Worker: SSA download → D1
packages/  shared/          Types, classification logic, HTML renderer — shared by all packages
migrations/        D1 SQL migrations (applied via wrangler d1 migrations apply)
scripts/  seed-from-shards.ts   One-shot initial D1 seeding from legacy JSON shards  verify-parity.ts      Pre-cutover parity checks vs legacy data
viz/               Legacy static site (GitHub Pages) — kept until DNS cutover

First-time setup

1. Provision Cloudflare resources

bash
# D1 databasewrangler d1 create name-vitals# Copy the database_id into both wrangler.toml files:#   apps/web/wrangler.toml#   apps/ingest-worker/wrangler.toml
# Queue (fan-out ingest)wrangler queues create name-ingestwrangler queues create name-ingest-dlq
# R2 bucket (SSA zip cache)wrangler r2 bucket create name-vitals-ingest

2. Apply schema

bash
wrangler d1 migrations apply name-vitals --remote

3. Seed initial data

Reads the existing viz/name-vitals/data/ JSON shards to populate D1 without pulling from the SSA:

bash
npm run seed# Apply each generated SQL file:ls migrations/seed/*.sql | sort | xargs -I{} wrangler d1 execute name-vitals --file={} --remote

4. Deploy

bash
npm run deploy:web       # deploy Cloudflare Pagesnpm run deploy:ingest    # deploy the cron Worker

5. Verify parity

bash
tsx scripts/verify-parity.ts --base=https://<preview>.pages.dev

Local development

bash
# Pages + Functions with local D1npm run dev:web
# Trigger the ingest cron locallynpm run dev:ingest          # starts wrangler dev# then: curl http://localhost:8787/run

Data refresh

The ingest Worker runs weekly (ETag-gated; exits immediately if the SSA zip is unchanged). The SSA publishes new data once a year, typically in May. Manual trigger:

bash
wrangler dev --test-scheduled   # local# or POST to the /run endpoint of the deployed Worker

GitHub Actions secrets

Required for the CI/CD workflows in .github/workflows/:

SecretValue
CLOUDFLARE_API_TOKENToken with Workers, Pages, and D1 write permissions
CLOUDFLARE_ACCOUNT_IDYour Cloudflare account ID

DNS cutover from GitHub Pages

After verifying parity on the Pages preview URL:

  1. Add a custom domain to the Pages project in the Cloudflare dashboard.
  2. Flip the DNS CNAME from the GitHub Pages address to the Cloudflare Pages CNAME.
  3. Add 301 redirects in the old GitHub Pages index.html from /babynames/viz/name-vitals/* to the new host.
  4. After ≥1 week of monitoring, delete viz/, dicts/, extra/, and any remaining legacy files.

License

Source data is CC0 (Social Security Administration). Code is MIT.

##Setup

This is a Node.js script, so you should consider downloading Node before attempting to run it.

To download the repo, simply clone it:

git clone https://github.com/TimeMagazine/babynames.gitcd babynames

Then install the dependencies:

npm install

##Data

First, you need to get the raw data from the Social Security Administration. This script will download and unzip it for you with the following command:

./index.js download 

###Total babies born each year

There is also a file called extra/totals.json with data on the total number of babies born (or at least, those issued a SSN) each year, per the SSA. This is useful because the totals are higher than the sum of each name in the name files, which don't include names that occur fewer than five times.

If you want to re-download the data--maybe it's a new year or you suspect there has been a revision--just run ./scripts/total_births.js, which will scrape the page on the SSA website and overwrite the file in the repo.

###Baby names

The Social Security Administration organizes the baby name data, somewhat inconveniently, as year-by-year text files named yob[year].txt. The above command extracts those files to a local directory named data/ and then deletes the zip file it downloaded. If you want to keep that zip file for some reason, just pass --cache to the command.

Once that's done, you can aggregate the data to a per-name basis and store it in a variety of formats:

./index.js store --format=json

First, the script reads every file and stores the data on a per-name basis in memory. For each name, it records both the absolute number of babies with that name in a given year and the percentage of all babies of the same gender with that name. The denominator in that calculation is the gender-specific total number of babies as reported on SSA.gov, NOT the calculated sum of all baby name frequencies (which will be lower than the actual number of children born in the United States, given that the data only counts names that appear at least five times). The years are stored as keys in an object for fast retrieval:

{  "_id": "Lothar-M",  "name": "Lothar",  "gender": "M",  "values": {    "1927": 7,    "1928": 6,    "1929": 10,    "1931": 6,    "1932": 8,    "1935": 8,    "1956": 7,    "1959": 5,    "1964": 6,    "1968": 5  },  "percents": {    "1927": 0.0000062135232896167586,    "1928": 0.000005418551494752584,    "1929": 0.000009301278646775573,    "1931": 0.000005775539435383265,    "1932": 0.000007664935030094451,    "1935": 0.00000768623999707923,    "1956": 0.0000033120134297413128,    "1959": 0.0000023436460007087187,    "1964": 0.000003010349581862443,    "1968": 0.0000028754074452349896  }}

###Formats

Your choices are:

  • json: Each name is stored as an individual JSON file in the /flat/individual/ directory.
  • jsonp: Each name is stored as an individual JSON-P file in the /flat/individual/ directory. It is wrapped in a callback function named ticallback by default, which you can override with opts.callback.
  • csvs: Each name is stored as an individual CSV file in the /flat/individual/ directory.
  • csv: All names are packaged into one CSV file and stored in /flat/names.csv/. This file will be able 30MB if you don't include limiting specifications (below). This preprocessed file is included in this repo.
  • mongodb: All names are inserted into a MongoDB instance. You are responsible for running a Mongo server at localhost:27017 or updating the source to point to your instance. Note: Because this is optional, the mongodb Node module is not listed as a dependency, you you'll need to install it yourself.

##Reducing the size As of 2013, there are 102,691 names that show up in at least one year at least five times. Many users will not be interested in this volume of data. There are several ways to reduce the scope with command line options.

###Limit the years

  • start: Don't retrieve years before this year. Ex: --start=1950. Default is 1880, the first year of the data.
  • end: Don't retrieve years after this year. Ex: --end=2000. Default is the present year.

###Exclude uncommon names

  • min: Don't include names that don't show up at least this many time in at least one year. Ex: --min=25. Default is 0.
  • cutoff: Don't include names that don't show up in at least this many individual years. Ex: --cutoff=50. Default is 0.

##Analysis

The script comes with several options for basic analysis:

  • normalize: Add a third property to each name that is the normalized value for the percentage figures, such that the peak percentage year is 1.
  • peaks: Find the peak value and year for both raw values and percents
  • maxima: Identify all the local maxima -- points where every value 5 years before and after is lower. Only counts maxima that are at least 25 percent of peak value.
  • pronunications: See if the name is listed in the CMU Pronouncing Dictionary. Require that you npm install cmudict manually.
  • dense: If a name does not appear in a year in the range specified between start and end, list that year in the data as 0. Otherwise it is not included at all (a "sparse" format).

##Types

For csv outputs, you can get the data back as either raw numbers of new babies each year with a given name (--type=values, which is the default) or as a percent (--type=values). JSON formats return both percents and values.

##Phonemes You can also pass a special type, --type=phonemes, to get back a JSON document of phoneme percents for each year for all names. By default, the script examines the first phoneme in each name. You can use --N==TK to aggregate around the TKth phonemes in the name. Use a negative value to start from the end.

##Extras We've now got British baby names going back to 1996, accessed on Oct. 5, 2016 from the U.K. Office for National Statistics. The total number of live births was downloaded here from the same source.

##License

This script is provided free and open-source by Time under the MIT license. If you use it, you are politely encouraged to acknowledge Time and link to this page.

The dictionary file dict/2of12.txt is from the 12 Dicts project, which is in the public domain.

來源:README.md,提交 abd9093

工具

12

search_names

Autocomplete search for US baby names. Returns up to 10 suggestions matching the given prefix.

輸入參數q必填

get_name_data

Returns full yearly birth count timeseries (1880–2025) for a given name for both sexes, including trend classification (rising/stable/declining/endangered/extinct), peak year, and peak count.

輸入參數name必填

get_names_by_status

Returns a curated list of names filtered by trend status.

輸入參數kind必填

get_year_names

Returns the top baby names for a given birth year (1880–2025).

輸入參數year必填

get_site_metadata

Returns top-10 names per year, total birth counts per year, and the full year range covered by the dataset.

無需輸入參數。

compare_names

Side-by-side comparison of 2-3 names: full yearly series for each so trends can be plotted or contrasted directly.

輸入參數names必填

get_name_twin

Finds the names whose popularity trajectory over time is most similar to the given name (cosine similarity on the yearly series), i.e. names that rose and fell together.

輸入參數sexname必填

get_decade_names

Returns the top baby names aggregated across an entire calendar decade.

輸入參數decade必填

get_year_movers

Year-over-year rank changes for the top 100 names of each sex vs. the prior year: biggest gainers, biggest losers, and new entrants.

輸入參數year必填

get_name_enrichment

Returns a precomputed profile for a name: estimated living population and median age, its popularity wave shape, cultural catalysts (events/media tied to spikes), historical demographic profiles by era (top occupations, region, urban vs. rural), and regional anomalies (states where it over-indexes).

輸入參數sexname必填

get_name_diaspora

Returns the geographic spread of a name over time: where it first broke out (a clearly higher rate there than nationally), when it peaked nationally, which states broke out and when, and which states never did. `neverAdopted` lists the states that never passed the breakout test; it does not mean the name had no bearers there. Names first recorded nationally in 1910 or earlier, before state records begin, list all 51 states because no origin can be observed.

輸入參數sexname必填

get_name_debuts

Returns every name that appeared in SSA records for the first time in the given year — genuine linguistic novelties, celebrity imports, invented spellings, or names newly crossing the 5-birth reporting threshold.

輸入參數year必填

版本歷史

1
  1. v1.0.0最新Sep 16, 2026

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