Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
Read-only Transport for London data: line status, arrivals, journeys, stop lookup.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
TFL_APP_KEY, TFL_MCP_MIN_INTERVAL_MSLos valores marcados como secretos son llaves de tu cuenta. Nunca los compartas ni los pegues en un chat.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en 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"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add tfl-ts --env TFL_APP_KEY=your-value --env TFL_MCP_MIN_INTERVAL_MS=your-value -- npx -y tfl-ts mcpCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.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"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"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"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
TFL_MCP_MIN_INTERVAL_MS envEsta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub ghcpuman902, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
Debes completar: TFL_APP_KEY
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (2.15.2) llegó al registro hace 22 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.
En la misma categoría: Spec Driven Development, Remote Desktop Commander, 好縮 Short
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Smart URL shortener: create, tag and track short links on s.gooo.name.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
Typed TfL client: friendly wrappers, 84 raw REST endpoints, and offline station topology for 20 rail lines.
Built with tfl-ts → Board
| tfl-ts | tfl-unified-api | tfl-journey-planner | tfl-mcp | mcp-tfl | |
|---|---|---|---|---|---|
| TypeScript types | Yes | No | No | Source only | Yes (src/index.ts) |
| Zero dependencies | Yes | No | No | No | No |
| Raw endpoint coverage | 84 | 10 of 84 | 1 of 84 | 59 of 84 | 8 of 84 |
| Offline station data | Yes | No | No | No | No |
| MCP support | Yes | No | No | Yes | Yes |
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.
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', });
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');
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).
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.
'central', 'victoria', 'elizabeth'. Not display names like 'Central'.'940GZZLUOXC'. Resolve with stopPoint.search() or place.search().'51800').LINE_NAMES, STATION_SEQUENCES, mode lists) before live calls.accidentStats and airQuality are deprecated.STATION_HUBS tracks Southeastern, South Western Railway, and similar operators for topology, but getArrivals() returns an empty array for them, not an error.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.sortLinesBySeverityAndOrder ranks it after incidents.lineId flips along shared track. Use withSharedTrackIdentity. Do not rewrite raw lineId.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.
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 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
Solo se muestra el principio; lee el resto en el repo