How to Use the CountryStateCity MCP in LangChain

Q: Can I use CountryStateCity with LangGraph state management?

Yes, you can pass the output of getcountry directly into your LangGraph state. This allows subsequent nodes in your graph to access verified ISO codes and country metadata without re-running the tool. It keeps your agentic workflows fast and predictable.

Q: Does listing cities require a paid subscription?

Yes, calling listcitiesbycountry requires a Supporter+ tier subscription. However, you can still use listcitiesbystate to pull city lists for specific states on the standard tier.

Feed verified global geographic data directly into your LangChain multi-step reasoning chains without writing manual API wrappers.

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Connect CountryStateCity MCP to LangChain

Create your Vinkius account to connect CountryStateCity 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 CountryStateCity with LangChain

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Map Regional Structures with LangChain

The CountryStateCity MCP Server provides direct access to global geographic structures for your LangChain chains. Your agent can call `list_countries` to find a target region, then immediately pass that output to `list_states` to build a complete state-level directory. This workflow bypasses hardcoded lookup tables by letting LangChain handle the sequence dynamically. We track every single transition in LangSmith. You can monitor exactly how your chain passes ISO codes from `get_country` to dependent tools, ensuring your agent never loses context between steps.

Dynamic City Resolution in ReAct Agents

This geographic MCP Server enables dynamic city resolution inside your ReAct agents. Let your agent decide when to query `list_cities_by_state` or `list_cities_by_country` based on the user's natural language input. The agent evaluates the intermediate results and chooses the precise geographic tool required for the next step. This execution pattern keeps your prompts clean. Instead of feeding massive JSON files of geographic data into your LLM context, your LangChain agent pulls only the specific city metadata it needs for the current run.

Trace ISO Code Extraction with LangSmith

This geographic data MCP Server allows you to track ISO code extraction with LangSmith. When your agent calls `get_state` to grab a region's ISO code, LangSmith traces the exact input and output parameters. You see the latency, token cost, and raw geographic payload in real-time. Integrating this MCP Server with your LangChain configuration takes about five minutes. You get clean, structured geographic data injected right where your chains need it, without the overhead of custom parser code.

Setup guide

Set up CountryStateCity 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 CountryStateCity 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({
    "countrystatecity-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 CountryStateCity 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 CountryStateCity. 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 CountryStateCity MCP in LangChain

You can configure standard LangChain retries or rate-limiting runnables around the MCP tool calls. When tools like `list_cities_by_state` hit limits, the agent handles the backoff gracefully. LangSmith will show these retry attempts clearly in your execution trace.

Yes, you can pass the output of `get_country` directly into your LangGraph state. This allows subsequent nodes in your graph to access verified ISO codes and country metadata without re-running the tool. It keeps your agentic workflows fast and predictable.

The LangChain MCP adapter automatically converts the JSON schema of tools like `get_state` into structured tool calls. Your agent reads the user's prompt, extracts the state name, and passes it as a clean argument. You don't have to write any manual parameter mapping.

Yes, calling `list_cities_by_country` requires a Supporter+ tier subscription. However, you can still use `list_cities_by_state` to pull city lists for specific states on the standard tier.

Your geographic queries, including country names and ISO codes, run inside an isolated, zero-trust V8 sandbox. We never log or store the specific locations, states, or cities your agent queries. The data passes through an ephemeral connection and is discarded immediately after the tool execution completes.

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