How to Use the Moova MCP in LangChain
Build LangChain chains that instantly book carriers using Moova's `create_shipment` tool and track packages with the Moova MCP Server.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Moova MCP to LangChain
Create your Vinkius account to connect Moova 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.
Multi-step shipping chains in LangChain
You can build a LangChain sequence where your agent retrieves shipping costs via Moova's `get_budget` tool and automatically passes that exact pricing to the `create_shipment` tool. This specific LangChain pipeline eliminates writing manual glue code between Moova's carrier selection and booking steps. LangSmith traces every step of this Moova workflow to show you the exact JSON payloads passed between `get_budget` and `create_shipment`. If a Moova address validation fails during the `create_shipment` tool execution, LangSmith highlights the exact field that caused the error.
Automated dispatch with LangChain ReAct agents
Give your LangChain ReAct agent the power to handle shipping exceptions using Moova's `update_shipment` and `cancel_shipment` tools. The LangChain agent evaluates live logistics data from Moova to decide whether to modify a delivery or cancel it entirely. By analyzing the current package status from Moova's `get_shipment_status` tool, the LangChain reasoning loop resolves delivery conflicts autonomously. This LangChain setup ensures that Moova shipments are updated via `update_shipment` before the carrier collects the package.
Live webhook sync via LangChain adapters
Connect your Moova webhook endpoints directly to LangChain event listeners using the `create_webhook` tool. When Moova triggers a delivery update, LangChain instantly kicks off a notification chain to alert your support team about the tracking state. You can monitor these event-driven Moova chains in LangSmith to track the execution times of `list_webhooks`. The LangChain adapter makes managing Moova's `delete_webhook` tool straightforward and highly observable.
Set up Moova MCP in LangChain
Prerequisites
- Python 3.10+ installed
-
langchain-mcp-adapters+langgraphpackages - 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 LangChainBaseToolobjects. - 2
Connect via HTTP transport
Use
MultiServerMCPClientwith"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 Moova tool calls through the MCP protocol. - 4
Run with any LLM
Swap
ChatOpenAIforChatAnthropic,ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.
from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI
async with MultiServerMCPClient({
"moova-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 Moova transactions"
})
print(result["messages"][-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Moova. 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 Moova MCP in LangChain
Use it with your favorite AI tools
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