Vinkius
ONS Discovery

Query 337+ UK Stats Datasets by ID and Filter.
Claude Claude
ChatGPT ChatGPT
Cursor Cursor
Gemini Gemini
Windsurf Windsurf
VS Code VS Code
JetBrains JetBrains
Vercel Vercel
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Works with every AI agent you already use

…and any MCP-compatible client

UK ONS Discovery — Search 337+ Statistical Datasets MCP on Cursor AI Code Editor MCP ClientUK ONS Discovery — Search 337+ Statistical Datasets MCP on Claude Desktop App MCP IntegrationUK ONS Discovery — Search 337+ Statistical Datasets MCP on OpenAI Agents SDK MCP CompatibleUK ONS Discovery — Search 337+ Statistical Datasets MCP on Visual Studio Code MCP Extension ClientUK ONS Discovery — Search 337+ Statistical Datasets MCP on GitHub Copilot AI Agent MCP IntegrationUK ONS Discovery — Search 337+ Statistical Datasets MCP on Google Gemini AI MCP IntegrationUK ONS Discovery — Search 337+ Statistical Datasets MCP on Lovable AI Development MCP ClientUK ONS Discovery — Search 337+ Statistical Datasets MCP on Mistral AI Agents MCP CompatibleUK ONS Discovery — Search 337+ Statistical Datasets MCP on Amazon AWS Bedrock MCP Support

Connect to your AI in seconds.

UK ONS Discovery — Search 337+ Statistical Datasets gives your AI agent direct access to the full Office for National Statistics catalog.

You search by keyword, browse metadata, validate filter variables using `get_dimension_options`, and execute flexible queries against any dataset ID. This handles all aspects of UK statistics—from housing prices to employment rates—in one place.

What your AI can do

Search datasets

Finds relevant dataset IDs, titles, and descriptions by running a keyword search across the entire ONS catalog.

List datasets

Browses the complete catalog of 337+ ONS datasets using paginated access.

Get dataset info

Retrieves the detailed metadata for a dataset ID, including its dimensions and editions.

+ 3 more capabilities included
Discover Datasets

Search 337+ datasets by keywords (e.g., 'economy', 'population') to find relevant dataset IDs.

Get Dataset Metadata

Retrieve the full details, methodology, and available versions for a specific ONS dataset ID using get_dataset_info.

Identify Filter Variables

Determine all possible dimension variables (like 'geography' or 'property-type') that can be used to filter the data.

Validate Dimension Values

Pull a list of valid options for any given filter variable, ensuring your query uses correct codes and ranges.

Query Observations

Execute the final data request using the dataset ID and all necessary dimension filters to retrieve structured data points.

Compatible AI Apps

OAuth 2.0 Compatible
Vinkius runs on Claude Claude
Vinkius runs on ChatGPT ChatGPT
Vinkius runs on Cursor Cursor
Vinkius runs on Gemini Gemini
Vinkius runs on VS Code VS Code
Vinkius runs on JetBrains JetBrains
Vinkius runs on Vercel Vercel
Vinkius runs on Zendesk Zendesk
+ any other MCP app
Included with Plan

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AI Agent

ONS Discovery: 6 Tools for Data Cataloging & Querying

Use this set of tools to move through the data lifecycle: find a dataset, validate its filters, and execute queries against structured ONS statistics.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using UK ONS Discovery — Search 337+ Statistical Datasets on Vinkius

Search Datasets

Finds relevant dataset IDs, titles, and descriptions by running a keyword search across the entire ONS catalog.

List Datasets

Browses the complete catalog of 337+ ONS datasets using paginated access.

Get Dataset Info

Retrieves the detailed metadata for a dataset ID, including its dimensions and...

Get Dimensions

Lists every available filter variable and its options that can be used to narrow...

Get Dimension Options

Pulls all valid filter values (codes) for a specific dimension within an ONS dataset.

Get Observations

Executes the final query, returning structured observations based on a dataset ID and specified filters.

Connect to your AI in seconds. Security and governance baked right in.

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Claude AI

Claude AI

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

3

Start a conversation

Open a new chat. The ONS Discovery integration is available immediately — no restart needed.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

  • Import from OpenAPI, Swagger, or YAML specs
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Start building

Make Your AI Do More

Start with UK ONS Discovery — Search 337+ Statistical Datasets, then connect any of our 5,000+ other servers whenever your AI needs more. One click, no limits.

  • Use this MCP plus 5,000+ others, all in one place
  • Add new capabilities to your AI anytime you want
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  • Works with Claude, ChatGPT, Cursor, and more
  • New servers added to the catalog every week
ONS Discovery MCP server cover

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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Works with Claude, ChatGPT, Cursor, and more

The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.

This connection provides 6 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.

Finding UK statistics shouldn't require a PhD in API Documentation.

Today, pulling a simple data comparison means navigating the ONS website. You click through dozens of departments (population, housing, employment). Then you find the right dataset PDF or download portal. Finally, you open an Excel sheet and spend hours cross-referencing dimension codes—like figuring out if 'Greater London' needs to be coded as GL or LND. It’s a massive amount of clicking and manual data cleaning.

With this MCP Server, your agent handles the whole mess. You just ask: 'What were house prices in X area?' The system uses `search_datasets` to find the ID, `get_dimensions` to validate the required filters, and finally runs `get_observations`. The result is clean, structured data, period.

Get Observations: Pulling actual data points with get_observations

The old way meant downloading a massive CSV file and then filtering it in Excel. If you needed to check a different time period or a slightly different region, you had to start the entire download process over again, wasting bandwidth and time.

Now, `get_observations` does the math for you. You provide the ID and filters; the server runs the query and gives back only what you asked for—a clean JSON data payload. It’s precise, fast, and repeatable.

What your AI can actually do with this

You're connecting your agent straight into the full Office for National Statistics catalog. Forget bouncing between different government sites or wading through dense PDF manuals; you handle every step—finding the data, validating the filters, and pulling the final numbers—all in one place.

Discovering the Right Dataset: You don't know what you need off the top of your head? Use search_datasets to run a quick search across 337+ datasets. Just drop keywords like 'housing' or 'population,' and it spits out relevant dataset IDs, titles, and descriptions. If you want to browse everything available without searching, list_datasets gives you paginated access to the whole catalog.

Getting Full Details: Once you have a promising ID, you gotta know exactly what that data is. You run get_dataset_info on the specific dataset ID; this retrieves all the detailed metadata for you, including methodology notes and every available edition of the data. This tool also shows you all the dimensions included in the set.

Setting Up Filters: Before you can pull anything, you gotta define your variables. You use get_dimensions to list every possible filter variable that dataset accepts—think 'geography' or 'property-type.' That tells you what you can filter by. But listing a dimension name isn't enough; you need the actual codes. For any specific dimension, run get_dimension_options.

This pulls all the valid codes and ranges for that variable, guaranteeing your query uses correct inputs.

Executing the Query: You've got the Dataset ID, and you’ve validated every filter code with get_dimensions and get_dimension_options. Now it's time to get the numbers. Execute get_observations. This tool runs the final query against ONS using your dataset ID and all the necessary filters you defined. It returns structured data points, ready for analysis.


This process keeps everything contained: search_datasets finds IDs based on keywords; list_datasets lets you browse the entire available catalog; get_dataset_info gives you methodology and dimensional details for an ID; get_dimensions maps out all potential filter variables; get_dimension_options validates specific codes for any variable; and finally, get_observations executes the query to return structured data points.

It's a complete workflow from zero knowledge to final numbers.

Built · Hosted · Managed by Vinkius ONS Discovery — Search 337+ UK Statistical Datasets MCP
Server ID 019d75e6-5890-73e9-a090-51b02111842a
Vinkius Inspector
Compliance Grade A+
Score 100/100
Vinkius Inspector Badge — Score 100/100

Questions you might have

How do I find a specific dataset using search_datasets? +

You give search_datasets the keywords (e.g., 'pension'). It returns matching IDs, titles, and descriptions from the 337+ catalog instantly.

What is the difference between get_dimensions and get_dimension_options? +

get_dimensions tells you what variables exist (like 'property-type'). get_dimension_options tells you the specific, valid values for that variable (e.g., 'detached', 'flat', 'semi-detached').

Can I query data without knowing the dataset ID? Use search_datasets. +

No. While search_datasets helps you find the ID, you must still use that specific ID when calling get_observations to run a valid query.

What do I use if I want to see all available datasets? Use list_datasets. +

list_datasets provides paginated access to the entire catalog. This is best used when you need an overview or suspect the dataset might be in a category you haven't guessed yet.

How does the get_dataset_info tool provide details about an ONS dataset's structure? +

It returns deep metadata for a dataset, showing its available dimensions, editions, and versions. You use this to understand the full scope of the data before you even try to query it.

When using get_observations, what is the best practice for querying time series data? +

You must specify the dimension filters along with the dataset ID. For a complete historical view, set the time filter parameter to =. This tells the system to pull the full available time range.

Before running a query, how should I use get_dimensions to understand necessary filter parameters? +

It lists every available dimension and shows what kind of filters you can apply. Check this tool first; it tells you what variables exist for filtering observations.

If I know the dimension but not its allowed values, what does get_dimension_options do? +

It retrieves every valid option value—like all geography codes or time periods—for a specific dimension. This prevents you from sending an invalid filter that would fail during observation querying.

How many datasets does the ONS have? +

The ONS API currently exposes 337+ datasets covering economy, population, health, trade, business, census, well-being, and more. New datasets are added regularly as part of the ONS Beta programme.

What format does the data come in? +

The API provides programmatic access to statistical observations in JSON format. It uses a hypermedia-driven architecture, nesting dimension links, options, and hierarchy information within the responses.

Is the API free to use? +

Yes, the ONS Developer API is completely free and open, requiring no authentication or API keys, allowing developers unrestricted access to UK national statistics.

Built & Managed by Vinkius 30s setup 6 tools

We've already built the connector for ONS Discovery. Just plug in your AI agents and start using Vinkius.

No hosting. No infrastructure. No complex setup.
All 6 tools are live and waiting. You're up and running in seconds.

Vinkius runs on Claude Claude
Vinkius runs on ChatGPT ChatGPT
Vinkius runs on Cursor Cursor
Vinkius runs on Gemini Gemini
Vinkius runs on Windsurf Windsurf
Vinkius runs on VS Code VS Code
Vinkius runs on JetBrains JetBrains
Vinkius runs on Vercel Vercel
+ other MCP clients

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