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How to Use the UK ONS Economy — GDP, Inflation & Consumer Spending MCP in LlamaIndex

Index and search UK ONS Economy — GDP, Inflation & Consumer Spending results with LlamaIndex.

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Connect UK ONS Economy — GDP, Inflation & Consumer Spending MCP to LlamaIndex

Create your Vinkius account to connect UK ONS Economy — GDP, Inflation & Consumer Spending 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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Searchable Economic Data Indexing

The `get_cpih` tool pulls the headline UK inflation measure. When you use this via LlamaIndex, the resulting CPIH data gets indexed into a vector store. You can then query past sessions to find out what the inflation rate was for specific periods. This means your RAG application isn't just running live calls; it’s combining live API results with historical knowledge, all searchable and grounded.

Retriving Consumer Spending Patterns

LlamaIndex helps you build a unified index from `get_retail_sales` and `get_spending_cards`. You can query across both datasets to understand the difference between overall retail sales volume and actual card spending patterns. Instead of just getting a list, you get answers grounded in the data. For example, 'What was the change in card spending vs. total retail sales in Q1 2023?'

Analyzing Tax Benefit Impacts

Need to know how tax redistribution affects income? Use `get_tax_benefits`. LlamaIndex ingests these statistics and makes them part of your knowledge base. You can then ask questions like, 'What are the effects of benefits on household income in a low-growth quarter?' The output becomes context for future queries, allowing deep semantic searches across multiple reports.

Setup guide

Set up UK ONS Economy — GDP, Inflation & Consumer Spending MCP in LlamaIndex

Prerequisites

  • Python 3.10+ installed
  • llama-index-tools-mcp package
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install dependencies

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

  2. 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. 3

    Convert to LlamaIndex tools

    Call mcp_tool_spec.to_tool_list_async() to convert all UK ONS Economy — GDP, Inflation & Consumer Spending MCP tools into native FunctionTool objects that any LlamaIndex agent can use.

  4. 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 UK ONS Economy — GDP, Inflation & Consumer Spending tools.",
)
response = await agent.run("List recent UK ONS Economy — GDP, Inflation & Consumer Spending data")

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by UK ONS. 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 UK ONS Economy — GDP, Inflation & Consumer Spending MCP in LlamaIndex

LlamaIndex indexes the output of tools like `get_gdp` into a vector store. You query past results—say, last year's regional GDP figures—and get answers grounded in actual API data.
The server provides everything from quarterly and annual regional GDP to real-time card spending indicators. You combine these structured tools with unstructured documents in one index.
Yes. Because the MCP tool output becomes part of a searchable knowledge base, you can query across vast time series data from tools like `get_retail_sales` and `get_cpih` easily.
It touches formal economic statistics: regional GDP records, CPIH inflation metrics, and detailed household income stats from tax benefits. All structured for indexing.
Yes. You can use the `allowed_tools` filter to restrict which economic datasets are included in your index, keeping your knowledge base focused on specific metrics like regional spending.

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