Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Beschreibung vom Entwickler (englisches Original)
Read-only Transport for London data: line status, arrivals, journeys, stop lookup.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
TFL_APP_KEY, TFL_MCP_MIN_INTERVAL_MSAls geheim markierte Werte sind Schlüssel zu deinem Konto. Gib sie nie weiter und füge sie nie in einen Chat ein.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"tfl-ts": {
"command": "npx",
"args": [
"-y",
"tfl-ts",
"mcp"
],
"env": {
"TFL_APP_KEY": "your-value",
"TFL_MCP_MIN_INTERVAL_MS": "your-value"
}
}
}
}Führe das in deinem Terminal aus
claude mcp add tfl-ts --env TFL_APP_KEY=your-value --env TFL_MCP_MIN_INTERVAL_MS=your-value -- npx -y tfl-ts mcpTrag die leeren Werte ein, bevor du ihn startest.
In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"tfl-ts": {
"command": "npx",
"args": [
"-y",
"tfl-ts",
"mcp"
],
"env": {
"TFL_APP_KEY": "your-value",
"TFL_MCP_MIN_INTERVAL_MS": "your-value"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"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"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
TFL_MCP_MIN_INTERVAL_MS envDiese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 7. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto ghcpuman902 bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Das musst du eintragen: TFL_APP_KEY
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (2.15.2) kam vor 22 Tagen in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Node.js auf deinem Computer.
In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, First Sale Scout
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
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.
Playbooks and a 14-day checklist for founders winning their first paying customers.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
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
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