How to Use the VesselAPI MCP in LangChain

Q: Can I audit vessel positions with VesselAPI and LangChain?

You absolutely can. You start by calling getvesselposition to get the latest AIS data. Then, you can chain that position check with searchvessels using the coordinates or name. This gives a verifiable log of when and where the vessel was located.

Q: What kind of scheduling info does VesselAPI provide for LangChain?

getvesselschedules pulls upcoming port calls and schedules for any given IMO number. Since you're using a chain, your agent can cross-reference these dates with the current API status via checkapistatus to warn you if there are potential delays.

Run complex maritime queries with LangChain agents.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect VesselAPI MCP to LangChain

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

GDPR Free for Subscribers

Setup VesselAPI with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Multi-Step Vessel Analysis for LangChain

Start by calling `check_api_status` to confirm the connection is live. You can then chain this status check into a sequence that calls `search_vessels` using the retrieved port list from `list_maritime_ports`. This creates an audit trail showing which data points you checked and when. This chaining ability lets your agent decide it needs more info. It might take the vessel name found in `search_vessels` and use that as input for a targeted call to `get_vessel_details`, building a full profile step by step.

MCP Server: Scheduling Chains

Build sequences around scheduling. First, the agent runs `list_maritime_ports` to see available destinations. Next, it uses a port name and vessel ID in `get_vessel_schedules`. You'll get all upcoming calls, which you can then feed into another tool call that checks for specific operational status using `check_api_status`. This makes sure the agent doesn't just report schedules; it validates them against current API requirements. It’s perfect for building automated port compliance workflows.

Real-Time Position Tracking Flow

Need to track a vessel? The flow begins with `search_vessels` to get the IMO number. You then pass that ID directly to `get_vessel_details` for static data, and immediately follow up by calling `get_vessel_position`. This gives your agent both the permanent specs and the live location in one go. It’s a clean chain: identify vessel -> get core details -> report current status. Your agent handles the handoff between these distinct calls automatically.

Setup guide

Set up VesselAPI MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes VesselAPI tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "vesselapi-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent VesselAPI transactions"
    })
    print(result["messages"][-1].content)

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 VesselAPI. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect VesselAPI now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about VesselAPI MCP in LangChain

LangChain lets you build multi-step reasoning pipelines. Instead of one shot, your agent decides it needs to call `search_vessels` first, then use the results to feed into `get_vessel_details`. It chains the outputs together for a complete picture.

You absolutely can. You start by calling `get_vessel_position` to get the latest AIS data. Then, you can chain that position check with `search_vessels` using the coordinates or name. This gives a verifiable log of when and where the vessel was located.

`get_vessel_schedules` pulls upcoming port calls and schedules for any given IMO number. Since you're using a chain, your agent can cross-reference these dates with the current API status via `check_api_status` to warn you if there are potential delays.

Yep. The server handles vessel names, IMO numbers, and AIS coordinates. Your agent can pull the name from `search_vessels` and use it to look up detailed schedules with `get_vessel_schedules`, combining different data domains into one output.

The server primarily handles vessel identification data, such as IMO numbers and vessel names. This is positional and descriptive metadata related to maritime movement.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript