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How to Use the UK ONS Discovery — Search 337+ Statistical Datasets MCP in Mastra AI

Build reliable data pipelines for UK ONS Discovery — Search 337+ Statistical Datasets with Mastra AI.

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Connect UK ONS Discovery — Search 337+ Statistical Datasets MCP to Mastra AI

Create your Vinkius account to connect UK ONS Discovery — Search 337+ Statistical Datasets to Mastra AI 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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Automate Multi-Step Data Retrieval

Building a complete data flow often fails due to missing parameters. With this MCP Server, your workflow can reliably chain calls: first `search_datasets`, then `get_dimensions` to validate filters, and finally `get_observations`. Mastra AI handles retries with exponential backoff if the initial query fails, ensuring your complex multi-step statistical analysis completes successfully.

Manage Dataset Metadata Changes

When a dataset updates its structure, you need to know. The `get_dataset_info` tool retrieves crucial metadata—like dimensions, editions, and versions—for any given ONS ID. This allows your workflow engine to check for changes before running a full data query, saving compute cycles and guaranteeing the latest information.

Browse and Select Datasets Automatically

Your agent doesn't need human input every time. It can list all available datasets using `list_datasets` or narrow them down with a keyword search via `search_datasets`. This lets you build autonomous background jobs that monitor the entire catalog of 337+ ONS statistical datasets.

Setup guide

Set up UK ONS Discovery — Search 337+ Statistical Datasets MCP in Mastra AI

Prerequisites

  • Node.js 18+ and a TypeScript project
  • @mastra/mcp + @mastra/core packages
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install dependencies

    Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).

  2. 2

    Configure the MCPClient

    Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.

  3. 3

    Discover and inject tools

    Call mcpClient.listTools() and spread the result into your agent's tools object. All UK ONS Discovery — Search 337+ Statistical Datasets tools become native Mastra tools.

  4. 4

    Run with any model

    Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts
import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "uk-ons-discovery-search-337-statistical-datasets-mcp-client",
  servers: {
    "uk-ons-discovery-search-337-statistical-datasets-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "UK ONS Discovery — Search 337+ Statistical Datasets Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to UK ONS Discovery — Search 337+ Statistical Datasets tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent UK ONS Discovery — Search 337+ Statistical Datasets transactions"
);
console.log(result.text);

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.

Why Choose Vinkius

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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

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Common questions about UK ONS Discovery — Search 337+ Statistical Datasets MCP in Mastra AI

Mastra AI's workflow engine lets you define conditional branching. For instance, if `get_dataset_info` shows a deprecated version, the workflow automatically retries using the latest available edition.
Yes. The server pulls from a broad catalog covering economy, population, health, and trade. Your agent treats them all as structured statistical datasets accessible via the same tools.
Definitely. You can design a workflow that sequentially checks `get_dimensions` for every necessary dimension before attempting to pull observations, making the process highly resilient.
Always start by calling `search_datasets` to confirm you have the right ID. This minimizes errors and ensures your subsequent calls to `get_observations` hit a valid target.
This MCP Server touches statistical datasets covering UK economic metrics, population figures, health statistics, and trade data.

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