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Census MCP Server

作者:cyanheads版本 0.7.2i★ –i电脑或云端
注册名称io.github.cyanheads/census-mcp-server

安装

概览

作者提供的说明(英文原文)

Query U.S. Census Bureau data, variables, and geography via MCP.

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。

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

你需要

  • 在云端运行无需安装任何东西,通过互联网连接
  • 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 …”。

适用于网页版、桌面版和手机版 Claude:

  1. 打开 Settings → Connectors
  2. 点击 Add custom connector
  3. 粘贴下面的地址,然后点击 Add
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Add2https://…3
https://census.caseyjhand.com/mcp

或者在你的电脑上运行

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "census": {
      "command": "npx",
      "args": [
        "-y",
        "@cyanheads/census-mcp-server"
      ],
      "env": {
        "CENSUS_API_KEY": "your-value",
        "MCP_LOG_LEVEL": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add --transport http census https://census.caseyjhand.com/mcp

或者在你的电脑上运行

claude mcp add census --env CENSUS_API_KEY=your-value --env MCP_LOG_LEVEL=your-value -- npx -y @cyanheads/census-mcp-server

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": {
    "census": {
      "url": "https://census.caseyjhand.com/mcp"
    }
  }
}

或者在你的电脑上运行

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": {
    "census": {
      "command": "npx",
      "args": [
        "-y",
        "@cyanheads/census-mcp-server"
      ],
      "env": {
        "CENSUS_API_KEY": "your-value",
        "MCP_LOG_LEVEL": "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": {
    "census": {
      "type": "http",
      "url": "https://census.caseyjhand.com/mcp"
    }
  }
}

或者在你的电脑上运行

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": {
    "census": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@cyanheads/census-mcp-server"
      ],
      "env": {
        "CENSUS_API_KEY": "your-value",
        "MCP_LOG_LEVEL": "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。

ChatGPT 只能连接互联网上的服务器:

  1. 打开网页版 ChatGPT → Settings → Connectors (Apps)
  2. 点击 Create 或 Add(部分套餐需要先在 Advanced 中开启 Developer mode)
  3. 粘贴下面的地址,起个名字,然后保存
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Create2https://…3
https://census.caseyjhand.com/mcp

菜单名称可能因套餐和版本不同而略有差异。

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

  • CENSUS_API_KEY env
    Census Bureau API key from api.census.gov/data/key_signup.html. Required for census_query_data and census_compare_geographies, and for census_list_predicate_values on a dimension it enumerates live;…
  • MCP_LOG_LEVEL env
    Sets the minimum log level for output (e.g., 'debug', 'info', 'warn').

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

工具名称和描述与服务器在 2026年11月6日 报告的完全一致。这些内容由作者撰写,不是我们写的;我们以纯文本形式显示。

  • census_list_datasets

    Browse available Census Bureau datasets with their supported vintage years. Use as the starting point when the right dataset is unknown — ACS5, ACS1, and their profile, subject, and comparison tables, population estimates, the decennial census files, and the business datasets (Co

  • census_list_geographies

    List the geography levels available for a given Census dataset and year, along with the parent geographies each level requires. Use before querying to confirm that the target geography level exists — ACS1 omits many sub-state levels, and not all datasets support tracts or block g

  • census_search_variables

    Search Census variables by keyword across variable labels and concept groups, or look one up by its code. Returns variable codes with human-readable labels — use this to go from a concept like "median household income" to the variable code B19013_001E needed for data queries. A q

  • census_get_variable

    Fetch full metadata for one or more Census variable codes — label, concept group, predicate type, the table's universe, and margin-of-error sibling references. Use to confirm a variable code before building a query, or to look up what a known code means. On ACS datasets it return

  • census_list_predicate_values

    List the codes a Census filter dimension accepts, so a predicates map can be written without guessing. Answers the question left open when census_query_data or census_compare_geographies reports that a dimension was left unset. Which route a dimension takes depends on the vintage

  • census_resolve_geography

    Resolve a place name, ZIP code, or street address to Census FIPS identifiers. Converts names like "King County, WA", "Seattle, WA", or "Seattle-Tacoma-Bellevue, WA", and ZIPs like "98109", to the codes required by census_query_data and census_compare_geographies. Use before query

  • census_query_data

    Query a Census dataset for one or more variables at one geography, a list of geographies at the same level, or every geography at a level. Accepts FIPS codes for the target geography — use census_resolve_geography to convert place names to FIPS when needed. On ACS datasets, label

  • census_compare_geographies

    Compare one or more variables across multiple geographies at the same level — all counties in a state, all states nationally, or a named set of specific geographies — ranked on the value of one of them. Covers queries like "compare median income across WA counties" or "which stat

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 cyanheads 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

  • ✓ 通过

    端点有响应

    在 239 毫秒内响应(HTTP 200)

  • – 不适用

    使用 OAuth 登录

    无需登录

  • ✓ 通过

    工具描述中没有隐藏指令

    已读取 8 个工具描述,未发现针对 AI 的隐藏指令

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32583 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32583 个服务器的 92% 更新
  • 基础检查结果等于或优于此分类中其他 32583 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

Census MCP Server 安全吗?

它在 3 项适用的基础检查中通过了 3 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?

两种方式都可以:安装在你的电脑上,或者连接云端版本。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.7.2)于3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。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, sync. labs

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

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
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Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211昨天更新
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sync. labs

作者:synchronicity-labs

Lipsync videos, dub them into other languages, make talking videos and open sync. Studio.

电脑或云端今天更新
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。

@cyanheads/census-mcp-server Query U.S. Census Bureau data, variables, and geography via MCP. STDIO or Streamable HTTP. 8 Tools

Public Hosted Server: https://census.caseyjhand.com/mcp


Overview

US Census Bureau demographic, economic, and housing data. Find datasets and variables, resolve place names or addresses to FIPS codes, and query or rank estimates across any set of geographies.

Tools
ToolDescription
census_list_datasetsBrowse available Census Bureau datasets (ACS5 and ACS1 with their profile, subject, and comparison tables, ACS Supplemental Estimates and Selected Population Profiles, Population Estimates, Decennial, County Business Patterns, Economic Census, Nonemployer Statistics) with vintage years and dataset codes.
census_list_geographiesList the geography levels supported by a dataset and year, with parent requirements and example FIPS values.
census_search_variablesKeyword search across variable labels and concept groups, or lookup by variable or table code. On ACS, returns estimate and margin-of-error codes together.
census_get_variableFetch full metadata for one or more variable codes — label, concept, predicate type, universe, MOE sibling — including the annotation and flag columns the data tools accept.
census_list_predicate_valuesList the codes a filter dimension accepts (EMPSZES, LFO, POPGROUP, NAICS2017…), from the dataset dictionary or a live wildcard enumeration.
census_resolve_geographyConvert place names (e.g., "King County, WA"), ZIP codes, or street addresses to Census FIPS identifiers via TIGERweb and Census Geocoder.
census_query_dataQuery a Census dataset for variables at one geography, a comma-separated list of them, or every geography at a level. Returns estimates with MOE, Census sentinel values and withheld business values resolved to their published meanings, and predicate filtering for the business datasets.
census_compare_geographiesRank and compare variables across multiple geographies — all counties in a state, all states nationally, or a named set. Sorted table output, with the same predicate filtering.

Capability reference

census_list_datasets tool
  • Returns dataset codes, names, descriptions, and available vintage years, with an optional keyword filter. Covers ACS5 and ACS1 (data profiles, subject tables, comparison profiles, and acs/acs1/spp), acs/acsse, Population Estimates, the 2020 Decennial files (Redistricting (P.L. 94-171), dec/dhc, dec/dp, dec/sdhc, dec/ddhca, dec/ddhcb), cbp, ecnbasic, and nonemp
  • Each description names the filter predicates the dataset requires and the geography levels it publishes
  • Dataset codes (e.g., acs/acs5) are what the other tools take. Case is ignored and a two-part code works by its last part alone (acs5, pl); three-part codes such as acs/acs5/profile must be given in full
  • available_years is exhaustive: any other year fails with year_not_available, naming the years that work

census_list_geographies tool
  • Returns one row per geography level and parent hierarchy: geography_level, whether a parent is required, required_parent_levels, and an example FIPS value. totalLevels counts each level once
  • geography_level values are the exact inputs to census_query_data and census_compare_geographies; year defaults to the latest vintage
  • Fails with dataset_not_found or year_not_available (naming the years served)

census_search_variables tool
  • Whole-word search across label and concept: every query word must match, otherwise the closest matches come back with a notice. A variable or table code in any case returns that variable, or the whole table in code order, first (B19013 returns B19013_001E then B19013_001M)
  • A code the dataset does not publish gets a notice naming the sibling dataset that holds it (S1701 in acs/acs5 points to acs/acs5/subject) or census_get_variable for an attribute column such as B19013_001EA
  • On ACS datasets, estimate (E suffix) and margin-of-error (M suffix) codes come back together; comparison profiles and the other families publish no margins of error. Also finds predicate codes by keyword (naics) or code (NAICS2017 in cbp)
  • limit is an integer from 1 to 100 (default 20), rejected rather than clamped when out of range. offset pages the complete match ordering; totalMatches counts matches before paging, truncated means another page exists, and nextOffset names it. variables.json is cached per dataset+year (default TTL 24h)

census_get_variable tool
  • Takes one or more variable codes (case-insensitive) and returns label, concept, predicate type, and the table's universe, in the order given. If groups.json can't be fetched, variables come back without universe and a notice says to retry
  • Resolves annotation and flag columns such as B19013_001EA and EMP_F, with attribute_of naming the column each belongs to and attribute_type its kind (ANNOTATION, FLAG, MARGIN_OF_ERROR). On ACS datasets it also returns estimate_code/moe_code sibling references
  • Confirms predicate dimension codes (NAICS2017, SEX) exist in a dataset; census_list_predicate_values lists their values. dataset defaults to acs/acs5 and year to the latest vintage
  • variable_not_found when a code isn't defined, naming the sibling dataset that publishes it when one is found (DP03_0062E in acs/acs5 points to acs/acs5/profile)

census_list_predicate_values tool
  • Lists the codes a filter dimension accepts, read from the dataset dictionary when it publishes a list and enumerated live otherwise. NAICS* and POPGROUP have long lists (thousands of codes; narrow with query); EMPSZES, LFO, RCPSZES, TAXSTAT, and TYPOP are live-only
  • Dictionary lists are checked against the rows the dataset actually publishes and unpublished codes are dropped; source says whether the check ran and the notice gives the number withheld. A dictionary list does not validate publication at a supplied geography level
  • Live enumeration takes geography_level (default us) and echoes that scope. Codes vary by level; only levels whose dataset metadata permits an unparented wildcard are accepted
  • query matches code and label; results are sorted by code before offset/limit paging (limit 1 to 500, default 50). totalCount counts all matches; truncated means another page exists, with nextOffset only then. On ecnbasic, within_naics scopes TAXSTAT and TYPOP to one industry
  • The live route and the dictionary check read the data endpoint, so they need CENSUS_API_KEY: without a working key a live-only dimension fails with missing_api_key, while a dictionary list still answers, unchecked, with a notice naming the key

census_resolve_geography tool
  • Named places (e.g., "King County, WA") resolve via TIGERweb; street addresses resolve to tract level via Census Geocoder, with block_group_fips and place_fips. A 5-digit ZIP (or ZIP+4) resolves to its ZIP Code Tabulation Area (zip code tabulation area)
  • Auto-detects geography_type for state, county, place, tract, and ZIP. Metropolitan/micropolitan statistical areas, combined statistical areas, consolidated cities, and economic places need an explicit geography_type; economic place returns the 8-digit ecnbasic code (Seattle 03363000)
  • The place level includes census-designated places, which answer a name only when no incorporated place or county matches exactly; use the full name ("Arlington CDP, VA") or geography_type: "place" to reach one. Optional county_fips scopes county and tract resolution (county_scope_unsupported for any other level or an address)
  • Matching ignores case, accepts a state abbreviation or full name, and tolerates Saint/St. and accent differences. New York City boroughs resolve to their counties ("Brooklyn, NY" → Kings County 047) with a notice
  • A name matching several geographies returns ambiguous_name with every candidate's FIPS code and state. Results carry state_fips (→ parent_fips) and fips_summary (→ geography_fips) for the next tool; statistical areas and ZCTAs omit state_fips

census_query_data tool
  • Requires FIPS codes (use census_resolve_geography for place names). geography_fips: "*" returns every geography at the level within the parent; each row carries geography_fips and the nationally unique geography_geoid. Wildcards return up to limit rows (default 50, max 500) in GEOID order, with offset for paging and totalCount for all matches. truncated is true only when another page exists; nextOffset names that page
  • A comma-separated list ("06,53", or "033,061" with parent_fips: "53") returns one row per listed code at the same level, in GEOID order and paged the same way; codes take the level's width, no "*" member, and the parents a single code needs. The notice names each listed code no row came back for
  • Up to 49 variable codes per call, fewer on datasets that add label or record columns (too_many_variables states the maximum). Unknown codes fail with variable_not_found; level and parent problems fail with parent_required or parent_not_accepted. Optional tract_fips (6 digits, with a concrete county_fips) scopes a block-group or decennial block query to one tract
  • Optional predicates map filters the business, pep, and dec datasets and acs/acs1/spp (e.g., {"NAICS2017": "5112"}). Unset dimensions take a Census default, echoed per row in applied_filters; "*" returns one row per category, labelled in record. pep/charv returns several rows per geography, so pin one (e.g., {"MONTH": "7"})
  • ACS se

只显示了开头部分;其余内容请在仓库中阅读

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