Which cities and countries does HERE Transit cover?

HERE Transit provides coverage in 70+ countries worldwide, including major cities in North America, Europe, Asia, South America, and Australia. Coverage includes bus, train, subway, tram, and ferry networks. Check coverage at developer.here.com for your specific city.

Is real-time transit data available through this MCP?

Yes! The schedule endpoint returns real-time departure and arrival estimates where available. Many transit agencies provide real-time GTFS-RT feeds that HERE integrates. Actual vs scheduled times are returned so you can see delays. Coverage varies by transit agency.

Can I plan wheelchair-accessible transit routes?

Yes! Use the get_station_details tool to check wheelchair accessibility for each station. Station details include elevator availability, step-free access, and accessibility amenities. Combine this with trip planning to ensure all transfer points are accessible for mobility-impaired travelers.

HERE Mobility MCP Server for CrewAI 8 tools — connect in under 2 minutes

Name: HERE Mobility
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 8 Tools Framework

Connect your CrewAI agents to HERE Mobility through the Vinkius — pass the Edge URL in the `mcps` parameter and every HERE Mobility tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="HERE Mobility Specialist",
    goal="Help users interact with HERE Mobility effectively",
    backstory=(
        "You are an expert at leveraging HERE Mobility tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token — get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in HERE Mobility "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 8 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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* 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 HERE Mobility MCP Server

What you can do

Connect AI agents to the HERE Transit API for comprehensive public transportation planning:

When paired with CrewAI, HERE Mobility becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call HERE Mobility tools autonomously — one agent queries data, another analyzes results, a third compiles reports — all orchestrated through the Vinkius with zero configuration overhead.

Discover transit trips between any two locations with bus, train, subway, tram, and ferry
Find nearby stations by GPS coordinates or name search
Get detailed route information with step-by-step transit instructions and transfers
Check departure/arrival schedules for any station in real-time
Plan multimodal journeys combining transit, walking, cycling, and scooter
Get station details including accessibility, amenities, and serving lines
Search trips with specific transport modes for customized travel preferences

The HERE Mobility MCP Server exposes 8 tools through the Vinkius. Connect it to CrewAI 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 HERE Mobility to CrewAI via MCP

Follow these steps to integrate the HERE Mobility MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py — CrewAI auto-discovers 8 tools from HERE Mobility

Why Use CrewAI with the HERE Mobility MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with HERE Mobility through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles — one agent researches, another analyzes, a third generates reports — each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass the Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

HERE Mobility + CrewAI Use Cases

Practical scenarios where CrewAI combined with the HERE Mobility MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries HERE Mobility for raw data, then a second analyst agent cross-references findings and flags anomalies — all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries HERE Mobility, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain HERE Mobility tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries HERE Mobility against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

HERE Mobility MCP Tools for CrewAI (8)

These 8 tools become available when you connect HERE Mobility to CrewAI via MCP:

discover_trips

Returns trip details including departure/arrival times, duration, number of transfers, and transport modes. Use origin and destination in lat,lng format. Optionally specify departure or arrival time in ISO 8601 format. Best for planning multimodal journeys. Discover public transit trips between origin and destination using HERE Transit API

get_nearby_stations

More precise than get_stations with customizable radius. Returns station IDs, names, distances, coordinates, and available lines. Use this for comprehensive station discovery in an area. Find all transit stations within a specific radius of coordinates

get_route_details

Requires the trip ID from a discover_trips result plus original origin/destination and departure time. Use this to review full route before traveling. Get detailed route information for a specific transit trip

get_schedule

Useful for checking when the next bus, train, or subway arrives. Requires station ID from get_stations result. Optionally filter by direction (e.g., "northbound", "downtown"). Get departure/arrival schedule for a specific transit station

get_station_details

Requires station ID from station search results. Use this to review station facilities before planning trips. Get detailed information about a specific transit station

get_stations

Returns station IDs, names, coordinates, and available transport lines. Use this to find stations before planning trips. Find transit stations near a GPS coordinate

get_stations_by_name

g., "Central Station", "Times Square"). Returns matching stations with IDs, names, coordinates, and available transport lines. Use this when you know the station name but not exact coordinates. Find transit stations by name

search_multimodal_trips

Modes can include: transit (bus/train/subway/tram/ferry), walk, bicycle, scooter, taxi. Returns multimodal route options with time breakdown per mode. Use this when user wants to combine walking or cycling with public transit for optimal journey. Search trips combining multiple transport modes (transit, walk, bike, scooter)

Example Prompts for HERE Mobility in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with HERE Mobility immediately.

"Find me the best public transit route from Brandenburg Gate to Berlin Central Station departing at 8am tomorrow"

"What buses and trains depart from Times Square in the next 30 minutes?"

"Plan a multimodal trip from my location combining subway and bike sharing"

Troubleshooting HERE Mobility MCP Server with CrewAI

Common issues when connecting HERE Mobility to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts — check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

The Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

HERE Mobility + CrewAI FAQ

Common questions about integrating HERE Mobility MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily — when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.