2,500+ MCP servers ready to use
Vinkius

Lyko MCP Server for Claude Code 12 tools — connect in under 2 minutes

Built by Vinkius GDPR 12 Tools CLI

Claude Code is Anthropic's agentic CLI for terminal-first development. Add Lyko as an MCP server in one command and Claude Code will discover every tool at runtime. ideal for automation pipelines, CI/CD integration, and headless workflows via Vinkius.

Vinkius supports streamable HTTP and SSE.

RecommendedModern Approach — Zero Configuration

Vinkius Desktop App

The modern way to manage MCP Servers — no config files, no terminal commands. Install Lyko and 2,500+ MCP Servers from a single visual interface.

Vinkius Desktop InterfaceVinkius Desktop InterfaceVinkius Desktop InterfaceVinkius Desktop Interface
Download Free Open SourceNo signup required
Classic Setup·bash
# Your Vinkius token. get it at cloud.vinkius.com
claude mcp add lyko --transport http "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
Lyko
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Lyko MCP Server

Connect your Lyko Transit API mobility platform to any AI agent and take full control of European public transit planning, real-time departure monitoring, and multimodal journey optimization through natural conversation.

Claude Code registers Lyko as an MCP server in a single terminal command. Once connected, Claude Code discovers all 12 tools at runtime and can call them headlessly. ideal for CI/CD pipelines, cron jobs, and automated workflows where Lyko data drives decisions without human intervention.

What you can do

  • Trip Planning — Plan door-to-door intermodal journeys combining buses, trains, subways, trams, ferries, bike-sharing, and walking
  • Real-Time Departures — Check upcoming departures at any transit stop with ETAs, platforms, and delay indicators
  • Arrival Tracking — Monitor incoming services for passenger pickup and connection coordination
  • Stop Discovery — Search transit stops by name, address, or landmark across 300+ European operators
  • Nearby Stops — Find all transit stops near any geographic location with distance calculations
  • Stop Details — Get comprehensive stop information including served lines, accessibility, and amenities
  • Line Information — Research transit lines with operator details, service hours, and route characteristics
  • Line Routes — View complete stop sequences and route patterns for any transit line
  • Operator Directory — Browse 300+ transit operators across Europe with coverage areas and service modes
  • Network Status — Check service disruptions, planned works, strikes, and delay alerts for any operator
  • GTFS Feeds — Access raw GTFS transit data for offline analysis and academic research
  • Trip Booking — Book train tickets, bus passes, bike rentals, and other mobility services through Lyko Book

The Lyko MCP Server exposes 12 tools through the Vinkius. Connect it to Claude Code in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Lyko to Claude Code via MCP

Follow these steps to integrate the Lyko MCP Server with Claude Code.

01

Install Claude Code

Run npm install -g @anthropic-ai/claude-code if not already installed

02

Add the MCP Server

Run the command above in your terminal

03

Verify the connection

Run claude mcp to list connected servers, or type /mcp inside a session

04

Start using Lyko

Ask Claude: "Using Lyko, show me...". 12 tools are ready

Why Use Claude Code with the Lyko MCP Server

Claude Code provides unique advantages when paired with Lyko through the Model Context Protocol.

01

Single-command setup: `claude mcp add` registers the server instantly. no config files to edit or applications to restart

02

Terminal-native workflow means MCP tools integrate seamlessly into shell scripts, CI/CD pipelines, and automated DevOps tasks

03

Claude Code runs headlessly, enabling unattended batch processing using Lyko tools in cron jobs or deployment scripts

04

Built by the same team that created the MCP protocol, ensuring first-class compatibility and the fastest adoption of new protocol features

Lyko + Claude Code Use Cases

Practical scenarios where Claude Code combined with the Lyko MCP Server delivers measurable value.

01

CI/CD integration: embed Lyko tool calls in your deployment pipeline to validate configurations or fetch secrets before shipping

02

Headless batch processing: schedule Claude Code to query Lyko nightly and generate reports without human intervention

03

Shell scripting: pipe Lyko outputs into other CLI tools for data transformation, filtering, and aggregation

04

Infrastructure monitoring: run Claude Code in a cron job to query Lyko status endpoints and alert on anomalies

Lyko MCP Tools for Claude Code (12)

These 12 tools become available when you connect Lyko to Claude Code via MCP:

01

book_trip

Supports booking train tickets, bus tickets, bike-sharing rentals, car-sharing reservations, and other mobility services available through the Lyko Book platform. Returns booking confirmation, payment details, ticket information, QR codes for validation, and cancellation policies. Availability and booking capabilities vary by operator and service type. Essential for Mobility-as-a-Service integration, ticket purchasing, service reservations, and end-to-end journey planning with booking. AI agents should use this when users ask "book this train ticket", "reserve a bike for this trip", or want to complete a mobility service reservation after planning a route. Book a transit trip or mobility service through Lyko Book

02

get_arrivals

Returns list of arriving services with line names and numbers, origins, scheduled and real-time arrival times (ETA), platform or bay information, delay indicators, and operator details. Essential for passenger pickup coordination, arrival monitoring, transit hub management, and real-time arrival boards. AI agents use this when users ask "when does the next train arrive at X", "show incoming services at this station", or need to track arriving services for passenger coordination. Get upcoming arrivals at a specific transit stop

03

get_departures

Returns list of departing services with line names and numbers, destinations, scheduled and real-time departure times (ETD), platform or bay information, delay indicators, and operator details. Supports buses, trains, trams, subways, and ferries across European transit networks. Essential for passenger information displays, departure boards, travel apps, and real-time transit monitoring. AI agents should reference this when users ask "when is the next bus from stop X", "show departures from this station", or need to monitor upcoming services at a known transit stop. Get next departures from a specific transit stop

04

get_line_info

Returns line name, number, type (bus, train, tram, subway, ferry), operator, color code, route description, service hours, frequency, and accessibility information. Essential for line identification, transit network exploration, service information queries, and route planning context. AI agents should reference this when users ask "tell me about line M1", "what operator runs bus line 42", or need line metadata to understand transit service characteristics. Get information about a specific transit line

05

get_line_routes

Returns route variants (e.g., direction A and B), complete stop sequences with order, scheduled frequencies, first and last service times, and any service variations (express vs. local, peak vs. off-peak). Essential for complete line visualization, stop sequence analysis, transit mapping, and understanding service patterns. AI agents use this when users ask "show me all stops on line X", "what is the full route of bus 42", or need to understand complete service patterns for a transit line. Get all routes and stops for a specific transit line

06

get_nearby_stops

Returns nearby stops with distances from the coordinate, stop names, locations, served lines, operators, and stop types, sorted by proximity. Essential for location-based transit discovery, passenger navigation, "stops near me" features, and geographic transit analysis. AI agents use this when users ask "what stops are near my current location", "find transit stops within 500m of these coordinates", or need to discover accessible transit options from a specific point. Find transit stops near a geographic location

07

get_network_status

Returns active service disruptions, planned works, line closures, delay information, weather impacts, strike notifications, and alternative service recommendations. Essential for real-time service monitoring, disruption awareness, passenger communication, and travel planning during service changes. AI agents should reference this when users ask "are there any disruptions on SNCF trains", "is the Berlin U-Bahn running normally", or need to check service reliability before planning trips. Get current network status and service alerts for a transit operator

08

get_operators

Returns operator names, IDs, countries, coverage areas, transport modes operated (bus, train, tram, subway, ferry), contact information, and service status. Covers 300+ operators across Europe including SNCF (France), DB (Germany), NS (Netherlands), RENFE (Spain), Trenitalia (Italy), and many regional and local operators. Essential for operator research, transit network scoping, country-specific transit analysis, and understanding service coverage. AI agents should use this when users ask "what transit operators are available in France", "list all train operators in Germany", or need to identify operators for a specific country or region. List public transit operators available in a country or region

09

get_stop_info

Returns stop name, location (latitude, longitude, address), served lines and routes, stop type (bus stop, train station, tram stop, subway station, ferry terminal), operator information, accessibility features (wheelchair access, elevators), and available amenities. Essential for stop identification, accessibility planning, transit network analysis, and passenger information. AI agents should use this when users ask "tell me about this stop", "what lines serve stop X", or need detailed stop metadata to contextualize transit queries. Get detailed information about a specific transit stop

10

get_transit_feed

Returns feed metadata, last update timestamp, included operators, coverage area, data freshness indicators, and download or access URLs. GTFS feeds contain static schedule data, route definitions, stop locations, fare information, and service calendars. Essential for transit data analysis, offline planning applications, academic research, and transit network visualization. AI agents use this when users need access to raw GTFS data, want to analyze transit schedules offline, or require complete network definitions for planning applications. Access GTFS transit feed data for a specific operator or region

11

plan_trip

Supports multiple transport modes including buses, trains, subways, trams, ferries, bike-sharing, car-sharing, and walking combinations. Returns complete itinerary with departure and arrival times, duration, number of transfers, legs with mode details (line name, operator, vehicle type), intermediate stops, walking distances, fares if available, and real-time delay information. Essential for travel planning, multimodal journey optimization, passenger information systems, and Mobility-as-a-Service (MaaS) applications. AI agents should use this when users ask "how do I get from X to Y by public transport", "plan a trip from Paris Gare du Nord to Versailles", or need intermodal route options with timing and transfer details. Plan an intermodal trip between two locations using public transit

12

search_stops

Returns matching stops with stop IDs, names, locations (latitude, longitude), served lines, operators, and stop types. Essential for stop discovery, journey planning interfaces, transit stop identification, and building location-based transit features. AI agents should use this when users ask "find the bus stop near Champs-Elysees", "search for stops called X", or need to identify stop IDs for use in departure/arrival queries. Search for transit stops by name or location

Example Prompts for Lyko in Claude Code

Ready-to-use prompts you can give your Claude Code agent to start working with Lyko immediately.

01

"Plan a trip from Paris Gare du Nord to the Palace of Versailles using public transit."

02

"Show me all departures from Berlin Alexanderplatz station in the next 30 minutes."

03

"What transit operators are available in the Netherlands, and is NS (Dutch Railways) running normally today?"

Troubleshooting Lyko MCP Server with Claude Code

Common issues when connecting Lyko to Claude Code through the Vinkius, and how to resolve them.

01

Command not found: claude

Ensure Claude Code is installed globally: npm install -g @anthropic-ai/claude-code
02

Connection timeout

Check your internet connection and verify the Edge URL is reachable

Lyko + Claude Code FAQ

Common questions about integrating Lyko MCP Server with Claude Code.

01

How do I add an MCP server to Claude Code?

Run claude mcp add --transport http "" in your terminal. Claude Code registers the server and discovers all tools immediately.
02

Can Claude Code run MCP tools in headless mode?

Yes. Claude Code supports non-interactive execution, making it ideal for scripts, cron jobs, and CI/CD pipelines that need MCP tool access.
03

How do I list all connected MCP servers?

Run claude mcp in your terminal to see all registered servers and their status, or type /mcp inside an active Claude Code session.

Connect Lyko to Claude Code

Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.