How to Use the NAICS/SIC Classification API MCP in LlamaIndex

Q: How do I index code definitions with the NAICS/SIC Classification API in LlamaIndex?

You pass the tools to a FunctionAgent. The agent queries the API for specific codes and writes the returned metadata into your document store as nodes.

Q: How do I connect the NAICS/SIC Classification API to LlamaIndex?

Install llama-index-tools-mcp and set up a BasicMCPClient. Wrap it with McpToolSpec and call the async tool list method to feed your agent.

Index federal industry taxonomies directly into your LlamaIndex RAG applications for grounded classification.

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Connect NAICS/SIC Classification API MCP to LlamaIndex

Create your Vinkius account to connect NAICS/SIC Classification API 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.

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Setup NAICS/SIC Classification API with LlamaIndex

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The `search_naics_codes` tool allows your LlamaIndex agent to query modern industry classifications and inject them straight into your vector store. You build RAG applications that actually understand federal tax codes instead of guessing them. When a user asks about manufacturing regulations, the engine pulls the exact hierarchical categories. This grounds your application in real government data.

Embed Full Taxonomy Metadata

Calling `get_classification_details` fetches the complete regulatory text for a specific code so your agent can index it. A raw code is useless to a semantic search engine without the underlying definitions. You pass this enriched text into your document store. Future queries about specific sectors will hit these exact definitions, ensuring your RAG pipeline returns accurate compliance answers.

Index Legacy SIC Systems

The `search_sic_codes` tool pulls the 1987 Standard Industrial Classification data for agents dealing with legacy financial documents. Older contracts reference these codes constantly, and your knowledge base needs to understand them. Before running a massive indexing job on historical records, your agent triggers `check_api_status`. This confirms the taxonomy endpoint is active before you waste compute resources on empty vector embeddings.

Setup guide

Set up NAICS/SIC Classification API 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 NAICS/SIC Classification API 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 NAICS/SIC Classification API tools.",
)
response = await agent.run("List recent NAICS/SIC Classification API data")

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Common questions about NAICS/SIC Classification API MCP in LlamaIndex

You pass the tools to a `FunctionAgent`. The agent queries the API for specific codes and writes the returned metadata into your document store as nodes.

Yes. Your agent can extract a vague industry description from an uploaded PDF, then query the MCP server to find the exact matching federal code.

Managing static files gets messy when building dynamic RAG apps. The API handles the exact text matching and filtering, keeping your vector store focused on semantic queries.

Install `llama-index-tools-mcp` and set up a `BasicMCPClient`. Wrap it with `McpToolSpec` and call the async tool list method to feed your agent.

The endpoints only process generic industry search terms and standard classification numbers. Your proprietary financial records stay local. The server simply matches your search strings against public taxonomy registries.

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