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tfl-ts

作者:ghcpuman902版本 2.15.2i★ –i在你的电脑上运行
注册名称io.github.ghcpuman902/tfl-ts

安装

概览

作者提供的说明(英文原文)

Read-only Transport for London data: line status, arrivals, journeys, stop lookup.

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: 其他
  • 你需要填写:TFL_APP_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: TFL_APP_KEY, TFL_MCP_MIN_INTERVAL_MS

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

  • 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": {
    "tfl-ts": {
      "command": "npx",
      "args": [
        "-y",
        "tfl-ts",
        "mcp"
      ],
      "env": {
        "TFL_APP_KEY": "your-value",
        "TFL_MCP_MIN_INTERVAL_MS": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add tfl-ts --env TFL_APP_KEY=your-value --env TFL_MCP_MIN_INTERVAL_MS=your-value -- npx -y tfl-ts 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": {
    "tfl-ts": {
      "command": "npx",
      "args": [
        "-y",
        "tfl-ts",
        "mcp"
      ],
      "env": {
        "TFL_APP_KEY": "your-value",
        "TFL_MCP_MIN_INTERVAL_MS": "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": {
    "tfl-ts": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "tfl-ts",
        "mcp"
      ],
      "env": {
        "TFL_APP_KEY": "your-value",
        "TFL_MCP_MIN_INTERVAL_MS": "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

  • TFL_APP_KEY 机密 必填 env
    TfL API primary key. Live tools need it. Static tools (docs, resolve_line_id, get_supported_modes) do not.
  • TFL_MCP_MIN_INTERVAL_MS env
    Minimum milliseconds between outbound TfL requests. Default 250. Cache hits do not count.

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 ghcpuman902 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“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 18444 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 18444 个服务器的 66% 更新
  • 基础检查结果等于或优于此分类中其他 18444 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

tfl-ts 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:TFL_APP_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(2.15.2)于23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:Spec Driven Development, Remote Desktop Commander, Egovframe Scaffold 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:↓ 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

Spec Driven Development

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

作者:formulahendry起步阶段↓ 66/周★ 44014个月前更新

在你的电脑上运行

Remote Desktop Commander

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

作者:desktop-commander正在增长★ 2113天前更新

在云端运行✓ desktopcommander.app

Egovframe Scaffold MCP

eGovFrame (전자정부 표준프레임워크) projects: templates, components, CRUD, build, 5.x migration, dependencies

作者:EricSeokgon起步阶段↓ 1440/周今天更新

在你的电脑上运行

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。

TfL API TypeScript Client

Typed TfL client: friendly wrappers, 84 raw REST endpoints, and offline station topology for 20 rail lines.

Built with tfl-ts → Board

How this compares

tfl-tstfl-unified-apitfl-journey-plannertfl-mcpmcp-tfl
TypeScript typesYesNoNoSource onlyYes (src/index.ts)
Zero dependenciesYesNoNoNoNo
Raw endpoint coverage8410 of 841 of 8459 of 848 of 84
Offline station dataYesNoNoNoNo
MCP supportYesNoNoYesYes

Counts use the 84 operations in the committed OpenAPI snapshot (ENDPOINT_COUNT in src/generated/endpoints.ts, pathCount in src/generated/openapi/spec.meta.json). Checked against each repo's source and the package.json published to npm on 16 October 2026.

tfl-ts publishes .d.ts files. Runtime dependencies: none. typescript is a peer dependency, for people compiling against the types. Station order and hubs ship in tfl-ts/meta, with no network call. tfl mcp is the local MCP server.

tfl-unified-api 2.0.2 is JavaScript, with no types field. It depends on moment, request, and request-promise-native. The Line module calls ten of the 84 paths: meta modes, severity, disruption categories, service types, route sequence, route by id, lines by mode, status by id, status over a date range, and status by mode. getRoutesByServiceType builds /Line/Route/{types}, which sits outside those 84 paths. db/lineColors.json is line colours, not stations.

tfl-journey-planner 1.1.2 is LiveScript compiled to JavaScript, with no types field. It depends on request and querystring. The module calls GET /Journey/JourneyResults/{from}/to/{to} only.

@daanrongen/tfl-mcp 1.4.3 is written in TypeScript. The published tarball is dist/main.js, package.json, and README.md, and package.json has no types field. It depends on @modelcontextprotocol/sdk, effect, and zod. Its tools call 59 of the 84 paths. They also call /Road/all/Disruption (the snapshot path is /Road/all/Disruption/{disruptionIds}), /Vehicle/EmissionSurcharge, and /Vehicle/UlezCompliance.

@pipeworx/mcp-tfl 0.1.2 sets "types": "src/index.ts", and that file is in the tarball. It depends on @modelcontextprotocol/sdk and tsx. Six tools call 8 of the 84 paths.

Station order ships with tfl-ts, in tfl-ts/meta.

Install and first call

Get a Primary key from the TfL API Portal. Subscribe to "500 Requests per min", then Profile → Show.

pnpm add tfl-ts

export TFL_APP_KEY=your-primary-key pnpm exec tfl raw line.statusByIds --ids victoria

[

{ "id": "victoria", "name": "Victoria", "lineStatuses": [{ "statusSeverityDescription": "Good Service" }] } ]

Line names, station order, and colours ship in the package. Status, arrivals, and journeys hit TfL at runtime.

On the portal you'll see two keys (Primary and Secondary); either works. app_id has been unused since Jan 2021.

Pass credentials in the constructor instead

const client = new TflClient({

appKey: 'your-primary-key', });

Quick starts

Node
import TflClient from 'tfl-ts';

const client = new TflClient(); // reads TFL_APP_KEY from process.env

const status = await client.line.getStatus({ modes: ['tube'] });

const arrivals = await client.stopPoint.getArrivals({ stopPointIds: ['940GZZLUOXC'], // Oxford Circus });

const journey = await client.journey.plan({ from: '940GZZLUOXC', to: '940GZZLUBND', });

const { matches } = await client.stopPoint.search({ query: 'Oxford Circus', modes: ['tube'], });

const busStops = await client.stopPoint.searchBusStops('Trafalgar Sq');

Next.js

Server Component with ISR (~60s). Boards and explorer: tfl-components · tfl.manglekuo.com/docs/explorer. Tube boards use official line colours; bus boards use route-number chips. Do not mix. See examples/README.md.

import TflClient, { sortLinesBySeverityAndOrder } from 'tfl-ts';

export const revalidate = 60;

const client = new TflClient(); const tube = await client.line.getStatus({ modes: ['tube'] }); const sorted = sortLinesBySeverityAndOrder(tube);

pnpm dlx shadcn@latest add https://tfl.manglekuo.com/r/tube-status-board.json

pnpm dlx shadcn@latest add https://tfl.manglekuo.com/r/tfl-roundel.json

The roundel ships a placeholder unless NEXT_PUBLIC_ALLOW_TFL_ROUNDEL=true (you accept trademark responsibility).

Agent / MCP

Read-only MCP (npx tfl-ts mcp), cached and rate-limited. Static tools never call TfL. The npm bin is tfl (dist/cjs/bin/tfl.js); mcp is the stdio subcommand. Setup: docs/mcp.md.

{

"mcpServers": { "tfl-ts": { "command": "npx", "args": ["-y", "tfl-ts@latest", "mcp"], "env": { "TFL_APP_KEY": "your-primary-key" } } } }

Tools: get_supported_modes, resolve_line_id, docs, resolve_stop_id, get_line_status, get_arrivals, plan_journey.

No repo access, or lost your context? npx tfl-ts docs ls lists every bundled agent doc (this README, CLAUDE.md, docs/agent.md, docs/mcp.md, …). docs cat prints one, and docs find / docs grep search across all of them — offline, no API key. The local MCP docs tool reads the same catalogue.

Gotchas

  • Line IDs are lowercase slugs: 'central', 'victoria', 'elizabeth'. Not display names like 'Central'.
  • Stop IDs look like '940GZZLUOXC'. Resolve with stopPoint.search() or place.search().
  • Bus stops accept 5-digit NaPTAN-style codes in search (for example '51800').
  • Prefer static constants (LINE_NAMES, STATION_SEQUENCES, mode lists) before live calls.
  • Cache status for about 30 to 60s. Do not poll arrivals faster than about 10 to 15s per stop.
  • accidentStats and airQuality are deprecated.
  • National Rail arrivals aren't live through TfL: STATION_HUBS tracks Southeastern, South Western Railway, and similar operators for topology, but getArrivals() returns an empty array for them, not an error.
  • Tube boards use official line colours; bus boards use route-number chips. Do not mix patterns.
  • Roundel trademark: placeholder unless the consumer opts in.
  • A line can carry several lineStatuses. Do not read [0]. Use getWorstCurrentStatus(line.lineStatuses) for the operative row.
  • validityPeriods[].isNow follows disruption.category === 'RealTime'. It is not a clock check. Planned engineering can be in force today with isNow: false.
  • validityPeriods[].toDate is the window end, not when trains resume. Weekend engineering often ends at 00:29Z (01:29 London, end of the traffic day). Overnight-split slices on one row are one possession; do not treat the first overlapping toDate as the next train.
  • Severity 20 is scheduled closure (Waterloo & City weekends, end of traffic day), not an unplanned Closed (1). sortLinesBySeverityAndOrder ranks it after incidents.
  • Circle / H&C / Met lineId flips along shared track. Use withSharedTrackIdentity. Do not rewrite raw lineId.

Before and after

getDetailedStatus() returns shorter types and renamed fields (severity, from, closureType, originName) instead of TfL's generated shapes:

const lines = await client.line.getDetailedStatus({

lineIds: ['bakerloo'], dateRange: { startDate: '2026-08-08', endDate: '2026-08-10' }, }); const s = lines[0]?.statuses?.[0]; s?.severity; s?.severityDescription; s?.validityPeriods?.[0]?.from; s?.disruption?.closureType;

Use getStatus({ detail: true }) or client.raw.line.* for exact TfL field names.

Station sequences

Tube, Elizabeth line, DLR, Overground, Tram, and river-bus pier topology. No credentials, no network. Identity, order, and branches only (no status or arrivals). River piers are not in STATION_HUBS — poll the NaptanFerryPort id. Live topology: client.line.getRouteSequence(). Also on the client: client.line.STATION_SEQUENCES.

import { LINE_STATION_SEQUENCES } from 'tfl-ts/meta';

const bakerloo = LINE_STATION_SEQUENCES.bakerloo; const outbound = bakerloo.orderedRoutes.find( (route) => route.direction === 'outbound' && route.serviceType === 'Regular', ); console.log(outbound?.stationIds, bakerloo.branches);

Station hubs and normalised arrivals

STATION_HUBS maps each physical station to its sibling StopPoint ids and the specific id that carries arrivals for each line — Liverpool Street's tube id (940GZZLULVT) and rail id (910GLIVST) both resolve to one HUBLST entry, with Central on the tube id and Elizabeth line on the rail id. No credentials, no network.

import { STATION_HUBS, resolveArrivalsStopId } from 'tfl-ts/meta';

const hub = STATION_HUBS['940GZZLULVT']; // any sibling id works const elizabethStopId = hub && resolveArrivalsStopId(hub, 'elizabeth'); // '910GLIVST'

resolveArrivalsStopId returns undefined when the hub doesn't carry that line, rather than the interchange id — polling the interchange id itself returns zero arrivals from TfL. Third-party National Rail operators (Southeastern, South Western Railway, c2c, and similar) show up in the hub's topology but never return live predictions: TfL's Arrivals API only covers tube, DLR, tram, Overground, and Elizabeth line.

client.stopPoint.getNormalizedArrivals() is getArrivals() plus a cleaned destination (falls through empty or literal "null" towards to destinationName, common on Elizabeth line, Overground, and some bus termini) and platform (compass bound, cleaned label, isUnknown for TfL's literal "Platform Unknown"):

const arrivals = await client.stopPoint.getNormalizedArrivals({

stopPointIds: ['940GZZLUOXC'], }); arrivals[0]?.destination.name; arrivals[0]?.platform.label;

getArrivals() and client.raw.* are unchanged.

client.stopPoint.get and getByGeoPoint lift Direction additional properties onto the stop: towards, compassPoint, and compassBearingDegrees. smsCode is filled from the first-class field or bag SmsCode. Facility keys stay in additionalProperties as TfL strings. parseAdditionalPropertyValue turns a bag value into null / boolean / number / date / text ("yes", "null", unix ms InstallDate). client.raw.stopPoint.* is unlifted. Do not use Prediction bearing (vehicle heading) as the stop flag; a painted `stopLette

只显示了开头部分;其余内容请在仓库中阅读

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