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.

UK ONS Discovery — Search 337+ Statistical Datasets MCP Server for CrewAI 6 tools — connect in under 2 minutes

Name: UK ONS Discovery — Search 337+ Statistical Datasets
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 6 Tools Framework

Connect your CrewAI agents to UK ONS Discovery — Search 337+ Statistical Datasets through the Vinkius — pass the Edge URL in the `mcps` parameter and every UK ONS Discovery — Search 337+ Statistical Datasets tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="UK ONS Discovery — Search 337+ Statistical Datasets Specialist",
    goal="Help users interact with UK ONS Discovery — Search 337+ Statistical Datasets effectively",
    backstory=(
        "You are an expert at leveraging UK ONS Discovery — Search 337+ Statistical Datasets tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token — get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in UK ONS Discovery — Search 337+ Statistical Datasets "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 6 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

UK ONS Discovery — Search 337+ Statistical Datasets

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About UK ONS Discovery — Search 337+ Statistical Datasets MCP Server

Full access to the ONS dataset catalog with discovery and query tools.

When paired with CrewAI, UK ONS Discovery — Search 337+ Statistical Datasets becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call UK ONS Discovery — Search 337+ Statistical Datasets tools autonomously — one agent queries data, another analyzes results, a third compiles reports — all orchestrated through the Vinkius with zero configuration overhead.

What you can do

Search — Find datasets by keyword
Browse — Paginated catalog access
Metadata — Dataset details, methodology, contacts
Dimensions — Available filter variables
Options — Valid values for each dimension
Query — Flexible observations with dimension filters

The UK ONS Discovery — Search 337+ Statistical Datasets MCP Server exposes 6 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect UK ONS Discovery — Search 337+ Statistical Datasets to CrewAI via MCP

Follow these steps to integrate the UK ONS Discovery — Search 337+ Statistical Datasets MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py — CrewAI auto-discovers 6 tools from UK ONS Discovery — Search 337+ Statistical Datasets

Why Use CrewAI with the UK ONS Discovery — Search 337+ Statistical Datasets MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with UK ONS Discovery — Search 337+ Statistical Datasets through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles — one agent researches, another analyzes, a third generates reports — each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass the Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

UK ONS Discovery — Search 337+ Statistical Datasets + CrewAI Use Cases

Practical scenarios where CrewAI combined with the UK ONS Discovery — Search 337+ Statistical Datasets MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries UK ONS Discovery — Search 337+ Statistical Datasets for raw data, then a second analyst agent cross-references findings and flags anomalies — all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries UK ONS Discovery — Search 337+ Statistical Datasets, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain UK ONS Discovery — Search 337+ Statistical Datasets tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries UK ONS Discovery — Search 337+ Statistical Datasets against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

UK ONS Discovery — Search 337+ Statistical Datasets MCP Tools for CrewAI (6)

These 6 tools become available when you connect UK ONS Discovery — Search 337+ Statistical Datasets to CrewAI via MCP:

get_dataset_info

Get metadata for an ONS dataset: dimensions, editions, versions

get_dimension_options

g., all geography codes, all time periods, all aggregate categories). Use this to find the correct filter values for observations. Get all option values for a specific dimension in an ONS dataset

get_dimensions

Each dimension has options you can use to filter observations. Essential for understanding what query parameters to use. Get available dimensions and filter options for an ONS dataset

get_observations

Provide dataset ID and dimension filters. Use search_datasets to find IDs and get_dimensions to discover available filters. Set time=* for full time series. Query any ONS dataset by ID with flexible dimension filters

list_datasets

The catalog contains 337+ datasets covering economy, population, health, trade, business, and more. Browse the complete ONS dataset catalog with pagination

search_datasets

Returns matching dataset IDs, titles, and descriptions. Use this to find the right dataset before querying data. Search ONS datasets by keyword — explore 337+ available datasets

Example Prompts for UK ONS Discovery — Search 337+ Statistical Datasets in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with UK ONS Discovery — Search 337+ Statistical Datasets immediately.

"What ONS datasets are available about housing?"

"Can you list the variables (dimensions) available for the house-prices dataset?"

"What is the latest data on the UK employment rate?"

Troubleshooting UK ONS Discovery — Search 337+ Statistical Datasets MCP Server with CrewAI

Common issues when connecting UK ONS Discovery — Search 337+ Statistical Datasets to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts — check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

The Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

UK ONS Discovery — Search 337+ Statistical Datasets + CrewAI FAQ

Common questions about integrating UK ONS Discovery — Search 337+ Statistical Datasets MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily — when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.