How to Use the HUD User (USPS Crosswalk) MCP in LlamaIndex

Q: How do I use HUD User (USPS Crosswalk) tools in LlamaIndex?

It's straightforward. Install llama-index-tools-mcp, create a BasicMCPClient with the server URL, and wrap it in an McpToolSpec. The spec exposes all tools like ziptocbsa for your LlamaIndex agent to use.

Q: Is it possible to select only specific tools, like ziptotract, for my LlamaIndex agent?

Yes. When you create the McpToolSpec, you can pass a list of tool names to the allowedtools filter. This gives you fine-grained control over what your agent is allowed to do, which is great for building specialized query engines.

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Connect HUD User (USPS Crosswalk) MCP to LlamaIndex

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Setup HUD User (USPS Crosswalk) with LlamaIndex

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Index Geographic Data Instantly

Use `zip_to_tract` to find all Census Tracts for a given ZIP code. LlamaIndex doesn't just show you the answer once. It adds that connection—the ZIP and its tracts—to a queryable knowledge index. This means the next time you ask a related question, your agent already has the context. It builds a map of these geographic relationships, making future queries faster and smarter without repeated API calls.

Build a Geographic Knowledge Base

Connect this MCP Server to LlamaIndex and start asking questions. As your agent uses tools like `zip_to_county` or `zip_to_cd`, it's not just fetching data; it's building a specialized knowledge base on the fly. Combine this with your own documents—like housing grant applications or site plans. Now you can ask complex questions that join your data with the official HUD User crosswalk data, all through a single query engine.

Query Past API Results

Let's say you ran a `county_to_zip` query last week. With LlamaIndex, that result is indexed. Today, you can ask 'Which ZIP codes did we look at in Fairfax County?' and get an answer instantly, without hitting the API again. Your agent's memory is grounded in the actual data it has worked with. This is perfect for analyzing past work, creating summaries, or just avoiding redundant API calls for data you've already fetched.

Setup guide

Set up HUD User (USPS Crosswalk) 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 HUD User (USPS Crosswalk) 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 HUD User (USPS Crosswalk) tools.",
)
response = await agent.run("List recent HUD User (USPS Crosswalk) data")

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Common questions about HUD User (USPS Crosswalk) MCP in LlamaIndex

It's straightforward. Install `llama-index-tools-mcp`, create a `BasicMCPClient` with the server URL, and wrap it in an `McpToolSpec`. The spec exposes all tools like `zip_to_cbsa` for your LlamaIndex agent to use.

Absolutely. That's the main use case for this MCP server with LlamaIndex. The tools provide the live, structured data, and LlamaIndex combines it with your unstructured documents to generate accurate, context-rich answers.

LlamaIndex automatically indexes the tool outputs. When your agent calls `cd_to_zip`, the resulting list of ZIP codes for that Congressional District becomes part of the knowledge graph, available for future semantic searches.

Yes. When you create the `McpToolSpec`, you can pass a list of tool names to the `allowed_tools` filter. This gives you fine-grained control over what your agent is allowed to do, which is great for building specialized query engines.

The server itself is stateless and only handles geographic codes like ZIPs and FIPS codes, never PII. All tool calls are made over a secure connection to the Vinkius sandbox. The data is only processed for your query and then discarded.

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