How to Use the TripGo MCP in CrewAI

Q: How does TripGo handle initial setup and regional validation with CrewAI?

The first agent should always call getregions. This confirms coverage across North America, Europe, Australia, etc. If the region is unsupported, the subsequent agents immediately halt operations.

Q: What happens if an agent needs to find a stop by name using TripGo and CrewAI?

The dedicated Search Agent uses searchstops. It takes the user's input (like 'Main St & 5th Ave') and returns matching stops, IDs, and relevance scores for other agents to use.

Q: If a trip fails during autonomous operation with TripGo and CrewAI, how do I handle it?

You can set up the crew hierarchy so that if plantrip returns zero options, an Escalation Agent is activated. This agent might then try finding alternative stops via getnearbystops.

Q: What data points does TripGo provide for detailed stop information with CrewAI?

The getstopdetails tool provides comprehensive information about a specific transit stop, including its facilities and operational capacity. This is crucial for the final agent to advise the user.

Q: What type of data does this server touch when running an autonomous TripGo operation with CrewAI?

This MCP Server handles stop IDs, coordinates, route names, and scheduled vs estimated times across all its tools.

Run full autonomous travel operations using a crew of specialized TripGo agents with CrewAI.

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Connect TripGo MCP to CrewAI

Create your Vinkius account to connect TripGo to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup TripGo with CrewAI

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Perplexity

Orchestrate complex trip planning autonomously.

You can assign one agent to run `get_nearby_stops` and another to call `plan_trip`. The crew works together: Agent A finds the nearest stop, hands that ID off to Agent B, which then calculates the best multimodal path. This collaborative approach ensures all necessary data points are covered without needing explicit human intervention at each step.

Monitor real-time vehicle status.

Assign a Monitoring Agent to constantly check `get_arrivals` and `get_departures`. This agent reports deviations immediately. A secondary Action Agent uses `get_vehicle_positions` for the latest map data, ensuring operational awareness. The crew handles continuous, asynchronous data streams.

Validate required transit infrastructure.

One agent researches coverage using `get_regions`. A second agent uses `get_route_info` to check the specific details of a route ID. If both checks pass, the third agent is authorized to proceed with calling `plan_trip`, confirming feasibility. This structured execution minimizes invalid requests.

Setup guide

Set up TripGo MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke TripGo tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="TripGo Analyst",
    goal="Access and analyze TripGo data via MCP.",
    backstory="Expert analyst with direct TripGo access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent TripGo transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="TripGo Analyst",
        goal="Access and analyze TripGo data via MCP.",
        backstory="Expert analyst with direct TripGo access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent TripGo transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by TripGo. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about TripGo MCP in CrewAI

The first agent should always call `get_regions`. This confirms coverage across North America, Europe, Australia, etc. If the region is unsupported, the subsequent agents immediately halt operations.

The dedicated Search Agent uses `search_stops`. It takes the user's input (like 'Main St & 5th Ave') and returns matching stops, IDs, and relevance scores for other agents to use.

You can set up the crew hierarchy so that if `plan_trip` returns zero options, an Escalation Agent is activated. This agent might then try finding alternative stops via `get_nearby_stops`.

The `get_stop_details` tool provides comprehensive information about a specific transit stop, including its facilities and operational capacity. This is crucial for the final agent to advise the user.

This MCP Server handles **stop IDs**, **coordinates**, **route names**, and **scheduled vs estimated times** across all its tools.

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