Bring Transit Planning
to CrewAI
Create your Vinkius account to connect TripGo to CrewAI and start using all 9 AI tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code. No hosting, no server setup — just connect and start using.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the TripGo MCP Server?
What you can do
Connect AI agents to the TripGo platform for intelligent multimodal journey planning:
- Plan trips combining bus, train, subway, tram, ferry, walking, and cycling
- Find nearby transit stops by GPS coordinates with distance and route info
- Search stops by name or address for precise location discovery
- Get real-time departures and arrivals with live delay estimates
- Track vehicle positions on the map with real-time GPS data
- Review route information including all stops and agency details
- Check stop details with accessibility and amenity information
- Access global regions covering major cities worldwide
How it works
- Get your TripGo API key from developer.tripgo.com (free tier available)
- Ask your AI agent to plan trips, check schedules, or track vehicles
- Natural language commands replace complex transit app navigation
- Multimodal planning combining public transit with active transportation modes
Who is this for?
Perfect for urban commuters, multimodal travelers, cyclists, pedestrians, transit riders, accessibility planners, and eco-conscious citizens. Let AI agents find optimal routes combining buses, trains, bikes, and walking. Ideal for daily commuters who want to compare route options, check real-time departures, track incoming vehicles, and plan sustainable journeys without car dependency.
Built-in capabilities (9)
Returns route names, origins, scheduled vs estimated arrival times, and delays. Use this to track incoming vehicles. Requires stop ID. Get upcoming arrivals to a transit stop
Returns route names, destinations, scheduled vs estimated departure times, and delays. Use this to check when your next ride arrives. Requires stop ID. Get upcoming departures from a transit stop
Returns stop IDs, names, coordinates, routes serving each stop, and distance from search point. Use this to find nearest transit options before planning trips. Find transit stops near a GPS coordinate
Each region has an ID, name, and coverage area. Use this first to verify your city is covered before planning trips. Supports major cities across North America, Europe, Australia, and Asia. List all available transit regions supported by TripGo
Requires route ID. Use this to understand route coverage before planning trips. Get information about a specific transit route
Requires stop ID from nearby stops or search results. Use this to review stop facilities before waiting there. Get detailed information about a specific transit stop
Optionally filter by route ID. Use this for real-time tracking of vehicles on the map. Get real-time vehicle positions for transit vehicles
Combines public transport (bus, train, subway, tram, ferry) with walking and cycling. Returns multiple trip options with departure/arrival times, duration, number of transfers, and step-by-step instructions. Optionally specify travel time and preferred transport modes. Plan a multimodal trip between two coordinates
g., "Times Square", "Main St & 5th Ave"). Returns matching stops with IDs, names, coordinates, routes, and relevance scores. Use this when you know the stop name or intersection but not exact coordinates. Search for transit stops by name or address
Why CrewAI?
When paired with CrewAI, TripGo becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call TripGo tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
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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
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CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the
mcpsparameter 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
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Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
TripGo in CrewAI
Why run TripGo with Vinkius?
The TripGo connection runs on our fully managed, secure cloud infrastructure. We handle the hosting, maintenance, and security so you don't have to deal with servers or code. All 9 tools are ready to work instantly without any complex setup.
You stay in complete control of your data. Your AI only accesses the information you approve, keeping your sensitive passwords and private details completely safe. Plus, with automatic optimizations, your AI works faster and more efficiently.
* Every connection is hosted and maintained by Vinkius. We handle the security, updates, and infrastructure so you don't have to write code or manage servers. See our infrastructure
Over 4,000 integrations ready for AI agents
Explore a vast library of pre-built integrations, optimized and ready to deploy.
Connect securely in under 30 seconds
Generate tokens to authenticate and link external services in a single step.
Complete visibility into every agent action
Audit live requests, latency, success rates, and active security compliance policies.
Optimize spending and track token ROI
Analyze real-time token consumption and cost metrics detailed by connection.
Explore our live AI Agents Analytics dashboard to see it all working
This dashboard is included when you connect TripGo using Vinkius. You will never be left in the dark about what your AI agents are doing with your tools.
TripGo and 4,000+ other AI tools. No hosting, no code, ready to use.
Professionals who connect TripGo to CrewAI through Vinkius don't need to write code, manage servers, or worry about security. Everything is pre-configured, secure, and runs automatically in the background.
Raw MCP | Vinkius | |
|---|---|---|
| Ready-to-use MCPs | Find and configure each manually | 4,000+ MCPs ready to use |
| Connection Setup | Manual coding & server setup | 1-click instant connection |
| Server Hosting | You host it yourself (needs 24/7 uptime) | 100% hosted & managed by Vinkius |
| Security & Privacy | Stored in plaintext config files | Bank-grade encrypted vault |
| Activity Visibility | Blind execution (no logs or tracking) | Live dashboard with real-time logs |
| Cost Control | Runaway AI token spend risk | Automatic budget limits |
| Revoking Access | Must delete files or code to stop | 1-click disconnect button |
How Vinkius secures
TripGo for CrewAI
Every request between CrewAI and TripGo is protected by our secure gateway. We automatically keep your sensitive data private, prevent unauthorized access, and let you disconnect instantly at any time.
Frequently asked questions
Which cities does TripGo cover?
TripGo covers major cities worldwide including Sydney, Melbourne, Brisbane, Auckland, Portland, and many more regions. Use the get_regions tool to see the complete list of supported areas. Coverage includes bus, train, tram, ferry, and bike share networks.
Does TripGo provide real-time transit data?
Yes! TripGo integrates real-time GTFS-RT feeds where available. The get_departures and get_arrivals tools return both scheduled and estimated real-time arrivals with delay information. Vehicle positions also provide live GPS coordinates when transit agencies broadcast them.
Can I plan bike-friendly multimodal routes?
Absolutely! Use the plan_trip tool with modes including 'bike' or 'bicycle' to find routes that combine cycling with public transit. TripGo will suggest bike-friendly paths, bike share stations, and transit connections that accommodate bicycles. Perfect for eco-conscious commuters.
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.
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
Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.
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