How to Use the Arrivy MCP in LangChain

Q: How do I verify the Arrivy connection in LangChain?

Run the getaccountcheck tool. It confirms your credentials are valid and the server is ready to process requests.

Build complex field service chains in LangChain using Arrivy tools to automate your last-mile delivery workflows.

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Connect Arrivy MCP to LangChain

Create your Vinkius account to connect Arrivy 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.

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Setup Arrivy with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Chain Arrivy tasks into logic pipelines

Connect `create_task` directly to your agent logic. Your agent evaluates current field data to trigger new service requests without human intervention. Chain these actions with other database calls in LangChain. The output from `list_tasks` feeds into your next step to ensure your schedule stays tight.

Sync crew availability in LangChain

Use `list_crews` to feed real-time personnel data into your agent. It knows exactly who is available before assigning a new job. This MCP Server provides the raw data your chain needs to make decisions. Your agent handles the logic, while Arrivy handles the heavy lifting of field management.

Manage customer records via LangChain

Pull your client base into your workflow using `list_customers`. Your agent parses this list to match specific jobs with the right contact details. Update status flags with `update_task` based on pipeline triggers. Your agent keeps the system clean and current.

Setup guide

Set up Arrivy 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 Arrivy 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({
    "arrivy-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 Arrivy transactions"
    })
    print(result["messages"][-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Arrivy. 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

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Common questions about Arrivy MCP in LangChain

Install the MCP adapters and point your client to the Vinkius endpoint. Once connected, your agent can call Arrivy functions directly within your defined chains.

Yes, you can build logic that lists current tasks and creates new ones based on your criteria. The agent handles the decision-making while Arrivy executes the field update.

Absolutely. You can fetch crew lists to assign work based on real-time availability in your LangChain pipeline.

Run the `get_account_check` tool. It confirms your credentials are valid and the server is ready to process requests.

We use encrypted transport for all data moving between your agent and Arrivy. Your sensitive customer names and contact records stay private through our isolated Vinkius sandbox.

Use it with your favorite AI tools

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

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