How to Use the Zippopotam.us MCP in LlamaIndex

Q: How do I use Zippopotam.us to improve my LlamaIndex knowledge base?

You run a tool call, like lookupnearbycity, and then pass the output directly to your indexing process. The resulting data becomes part of your searchable vector store, making that information permanent for later queries.

Build RAG systems that index location knowledge with LlamaIndex.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Zippopotam.us MCP to LlamaIndex

Create your Vinkius account to connect Zippopotam.us to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Zippopotam.us with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Indexing city data.

You run `lookup_nearby_city` and get a list of zip codes for a given metro area. Instead of just displaying it, your agent indexes this result into the vector store. This means you can search past sessions using semantic queries against that exact API output. Later, you query your knowledge base—'What were the zips I found for Chicago last week?'—and get an answer grounded in actual data, not guesses.

Search by postal code results.

The `lookup_postcode` tool resolves a specific zip code into coordinates and location details. By passing this structured output to LlamaIndex, you augment your knowledge base with verified geographical facts. This is perfect for creating operational manuals or FAQs where the answer must be tied back to a verifiable source like Zippopotam.us.

Combining documents and API data.

LlamaIndex allows you to merge your company PDFs with live API calls. You might read a document mentioning 'the area around 90210'. Your agent uses `lookup_postcode`, indexes the resulting coordinates, and then combines that data with the text in the PDF for one unified answer. This creates powerful RAG applications where documents and real-time API results live together in the same searchable index.

Setup guide

Set up Zippopotam.us MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Zippopotam.us MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Zippopotam.us tools.",
)
response = await agent.run("List recent Zippopotam.us data")

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Zippopotam.us. 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.

Connect Zippopotam.us now

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 Zippopotam.us MCP in LlamaIndex

You run a tool call, like `lookup_nearby_city`, and then pass the output directly to your indexing process. The resulting data becomes part of your searchable vector store, making that information permanent for later queries.

Yes. Since the tool output is indexed into a knowledge base, you can query past results from `lookup_postcode` or other tools. You get answers grounded in what was actually returned by the MCP Server.

The server provides structured geographical identifiers: zip codes, city names, state information, and coordinates. These are the specific types of data you'll be indexing into your knowledge base.

It is built to provide structured intelligence. If you query a known zip code, `lookup_postcode` gives precise results that are excellent sources of truth for your RAG application.

The server touches geographical identifiers, specifically city names and postal codes. Your AI client connects via a secure endpoint token to maintain the integrity of this data.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript