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ONS + Nomis MCP server

ONS + Nomis MCP server

by brynmrgn
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Remote

nomis_search_datasets

Search Nomis census and labour-market datasets by keyword. Returns dataset ID, name, description, and dimension details for data retrieval.

Instructions

Search Nomis census / labour-market datasets by keyword.

Matches query (case-insensitive substring) against dataset id, name and description across the whole Nomis catalogue. Returns each dataset's id (e.g. NM_1_1), name, description and the list of its dimensions with the conceptref you pass as a query param to nomis_get_data. Nomis covers Claimant Count, APS, Census 2011/2021 tables, workforce jobs and more — data the ONS beta API lacks.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "nomis_search_datasets"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
queryYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, but description fully covers behavioral traits: read-only search, case-insensitive substring matching, returns dataset details and dimensions with conceptref, and mentions catalogue-wide scope.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Concise and well-structured: first sentence states purpose, then explains matching, return format, and context. No superfluous information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Describes input (query) and output (dataset id, name, description, dimensions with conceptref) adequately, and provides coverage context. Missing explanation of limit, but output schema likely covers return details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Description explains the `query` parameter (case-insensitive substring) but does not mention the `limit` parameter or its default, despite 0% schema description coverage requiring compensation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the tool searches Nomis datasets by keyword, specifies matching across id, name, and description, and distinguishes from siblings by targeting Nomis coverage.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides clear context for when to use (searching Nomis datasets) and contrasts with ONS beta API, but lacks explicit alternatives or when-not-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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