How to Use the Smarty MCP in LangChain
Build complex, multi-step data flows for LangChain.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Smarty MCP to LangChain
Create your Vinkius account to connect Smarty to LangChain — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.
Key Capabilities
Sequential Address Processing
Need to clean up messy text before validation? Use `extract_addresses` to pull out all potential physical addresses. Then, you can pipe those results into a specific validator like `validate_us_address`. This lets your agent first identify the data and then pass it off for DPV status checks.
US vs. International Routing
Your agent needs to know which tool to call? Use a routing step based on input patterns. First, call `autocomplete_us_address` if the input looks like a US address. If it's international, run `autocomplete_intl_address`. The output of that autocomplete becomes the input for the specific validation tool.
Data Integrity Checks
Before committing data, check everything. An agent can first use `get_account_info` to confirm user permissions. After that, it runs `verify_zip_code` on a given zip code just to make sure the associated city and state haven't changed. It’s simple multi-step verification.
Set up Smarty 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 Smarty 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({
"smarty-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 Smarty 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 Smarty. 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.
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 Smarty MCP in LangChain
Use it with your favorite AI tools
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Start using the Smarty MCP today
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