Can the AI find an address hidden inside a block of text automatically?

Yes! You can paste an entire email string or customer support note into your prompt and ask the AI: 'Extract any addresses mentioned in this text.' The agent triggers the `extract_addresses` engine to return the geolocated and sanitized address format purely.

How accurate is the address verification?

Smarty ensures the address is validated against official sources like the USPS using DPV (Delivery Point Validation) for US requests, guaranteeing a package can actually be delivered to the mapped coordinate. Your AI agent returns this rigorous underlying metadata.

Can I use the agent to fix my dataset dynamically without coding?

Yes. If you have 20 poorly formatted customer addresses, you can simply paste them in the prompt, asking your AI to 'Run each of these through Smarty and return a markdown table of the normalized addresses.' The agent handles the iteration loop for you via the tools.

Smarty MCP Server for LangChain 7 tools — connect in under 2 minutes

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 7 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Smarty through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "smarty": {
            "transport": "streamable_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,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Smarty, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Smarty MCP Server

Connect your Smarty account to any AI agent and empower your team to sanitize raw address data, query ZIP codes, and format global street locations securely. Interact with powerful geospatial and mailing validation APIs through natural language without writing a single line of custom script.

LangChain's ecosystem of 500+ components combines seamlessly with Smarty through native MCP adapters. Connect 7 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

What you can do

Address Validation (USA/Intl) — Effortlessly clean and verify messy user inputs calling validate_us_address, returning the Delivery Point Validation (DPV)
Text Extraction — Feed your AI unformatted text like emails or notes and run extract_addresses to intelligently isolate real physical addresses
Autocompletion Tests — Interrogate the AI dynamically with partial street names using the autocomplete_us_address algorithm
ZIP Code Checks — Validate specific 5-digit postal zones using verify_zip_code to retrieve associated municipal limits

The Smarty MCP Server exposes 7 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Smarty to LangChain via MCP

Follow these steps to integrate the Smarty MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 7 tools from Smarty via MCP

Why Use LangChain with the Smarty MCP Server

LangChain provides unique advantages when paired with Smarty through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Smarty MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Smarty queries for multi-turn workflows

Smarty + LangChain Use Cases

Practical scenarios where LangChain combined with the Smarty MCP Server delivers measurable value.

RAG with live data: combine Smarty tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Smarty, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Smarty tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Smarty tool call, measure latency, and optimize your agent's performance

Smarty MCP Tools for LangChain (7)

These 7 tools become available when you connect Smarty to LangChain via MCP:

autocomplete_intl_address

Predictive autocomplete for international addresses

autocomplete_us_address

Predictive autocomplete for US addresses

extract_addresses

g., emails, documents) and find valid addresses. Extracts physical addresses from raw text

get_account_info

Retrieves Smarty account information

validate_intl_address

Requires at least the address line and country. Validates and geocodes an international street address

validate_us_address

Returns delivery point validation (DPV) status and coordinates. Validates and geocodes a US street address

verify_zip_code

Verifies a ZIP code and returns associated cities and states

Example Prompts for Smarty in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Smarty immediately.

"Validate this US address: 1 Santa Claus Ln, North Pole, AK 99705."

"Can you extract any known addresses from this raw text string: "I live out near the big oak tree at 1600 Amphitheatre Pkwy, Mountain View, CA 94043, come visit soon!""

"Provide a markdown list of US autocomplete suggestions when a user types "3311 w 300 s s"."

Troubleshooting Smarty MCP Server with LangChain

Common issues when connecting Smarty to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Smarty + LangChain FAQ

Common questions about integrating Smarty MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.