How to Use the ZIP Codes API MCP in LangChain

Q: Can I use the ZIP Codes API with LangChain for distance checks?

Absolutely. You can chain together calls starting with findzipsbycounty and then passing pairs of those resulting codes to getzipdistance. This lets you measure distances across large, defined regions.

Q: Does the ZIP Codes API support finding codes by radius when using LangChain?

Yes, you can use findzipsinradius. You give it a starting ZIP code and a mile count, and the agent returns all associated ZIPs. It's perfect for localized area audits.

Q: What is the best way to combine state data and county data with ZIP Codes API using LangChain?

You can start broad by calling findzipsbystate. Then, you filter that list down by running a secondary search against findzipsbycounty for specific areas.

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Setup ZIP Codes API with LangChain

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Chaining Location Data Lookups

You can find all ZIP codes for a given area using `find_zips_by_city`. Then, you pass that list of initial results to `get_zip_details` in the next step. The agent builds this sequence automatically. This multi-step approach means your code isn't just calling one tool; it's running a full pipeline where output determines what input comes next.

Calculating Distance Chains

Need to audit locations? Start by finding initial ZIP codes using `find_zips_by_county`. Next, pass pairs of those results into `get_zip_distance` to calculate the separation. The resulting distance data can then feed into another tool call. This lets you create complex reasoning chains that verify geographical relationships across multiple steps.

MCP Server for Complex Audits

Use `find_zips_by_state` to get a broad set of codes. Then, filter and narrow the search by running `find_zips_in_radius` against a specific starting point. The overall flow lets you audit large regions down to small, precise areas. It handles the entire logic sequence, letting your agent decide which combination of location tools makes sense for the user's request.

Setup guide

Set up ZIP Codes API 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 ZIP Codes API 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({
    "zip-codes-api-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 ZIP Codes API transactions"
    })
    print(result["messages"][-1].content)

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Common questions about ZIP Codes API MCP in LangChain

LangChain lets you build sequences where one tool's output feeds directly into another. For example, you can find all ZIP codes in a state using `find_zips_by_state`, and then immediately pass those results to get demographic details for each code.

Absolutely. You can chain together calls starting with `find_zips_by_county` and then passing pairs of those resulting codes to `get_zip_distance`. This lets you measure distances across large, defined regions.

This MCP Server deals primarily with Location and Demographic data types. You're reading static geographic information like state boundaries, county names, and detailed population metrics for specific codes.

Yes, you can use `find_zips_in_radius`. You give it a starting ZIP code and a mile count, and the agent returns all associated ZIPs. It's perfect for localized area audits.

You can start broad by calling `find_zips_by_state`. Then, you filter that list down by running a secondary search against `find_zips_by_county` for specific areas.

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