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OECD MCP Server

npm version MCP Registry MCP Protocol License

A Model Context Protocol (MCP) server providing AI assistants access to OECD's 5,000+ economic and statistical datasets via SDMX API. By connecting to the MCP server, you can use AI to search, analyze, and compare data from 38 OECD countries across economy, health, education, environment, and more.

En Model Context Protocol (MCP) server som ger AI-assistenter tillgång till OECD:s 5,000+ ekonomiska och statistiska dataset via SDMX API. Genom att ansluta till MCP-servern kan du med hjälp av AI söka, analysera och jämföra data från 38 OECD-länder inom ekonomi, hälsa, utbildning, miljö och mer.


Quick Start

Det är enkelt att ansluta en LLM / AI-chatbot till MCP-servern. Det enklaste sättet är att använda npm-paketet oecd-mcp via npx. Nedan finner du guider för olika klienter.

The easiest way to connect an LLM / AI chatbot to the MCP server is via the published npm package oecd-mcp using npx. Below you'll find guides for different clients.


Claude Desktop

1. Open Claude Desktop settings → Developer → "Edit Config"

2. Add to the JSON file:

{
  "mcpServers": {
    "oecd": {
      "command": "npx",
      "args": ["-y", "oecd-mcp"]
    }
  }
}

3. Save and restart Claude Desktop


Claude Code

claude mcp add oecd npx -y oecd-mcp

Verify: claude mcp list


OpenAI Codex

~/.codex/config.toml:

[mcp.oecd]
command = "npx"
args = ["-y", "oecd-mcp"]
transport = "stdio"

From Source

git clone https://github.com/isakskogstad/OECD-MCP.git
cd OECD-MCP
npm install
npm run build

Then point your client at node /absolute/path/to/OECD-MCP/dist/index.js, e.g.:

{
  "mcpServers": {
    "oecd": {
      "command": "node",
      "args": ["/absolute/path/to/OECD-MCP/dist/index.js"]
    }
  }
}

Related MCP server: WHO MCP Server

Features

Servern ansluter till OECD SDMX API och ger tillgång till 5,000+ dataset i 17 kategorier.

OECD SDMX API Tillgång till kvartalsvis nationalräkenskaper (QNA), huvudsakliga ekonomiska indikatorer (MEI), hälsostatistik, utbildningsdata, miljöindikatorer och mer från 38 OECD-medlemsländer plus partnerekonomier.

MCP-servern implementerar MCP-protokollet med stöd för:

  • 9 verktyg — Dataset-upptäckt (5) och dataåtkomst (4)

  • 7 resurser — Kategorier, länder, filterguide, ordlista, LLM-instruktioner

  • 7 promptmallar — Ekonomisk analys, landsjämförelser, nordiskt fokus

The server connects to the OECD SDMX API providing access to 5,000+ datasets across 17 categories:

OECD SDMX API Access to quarterly national accounts (QNA), main economic indicators (MEI), health statistics, education data, environmental indicators, and more from 38 OECD member countries plus partner economies.

The MCP server implements the MCP protocol with support for:

  • 9 tools — Dataset discovery (5) and data access (4)

  • 7 resources — Categories, countries, filter guide, glossary, LLM instructions

  • 7 prompt templates — Economic analysis, country comparisons, Nordic focus

Tools

Tool

Description

search_dataflows

Search for datasets by keyword

list_dataflows

List datasets by category

get_categories

List all 17 data categories

get_popular_datasets

Get commonly used datasets

search_indicators

Search for specific indicators

get_data_structure

Get metadata for a dataset

query_data

Query statistical data

get_dataflow_url

Generate OECD Data Explorer link

list_categories_detailed

Detailed category information

Resources

Resource

Description

oecd://categories

17 data categories with descriptions

oecd://dataflows/popular

Curated popular datasets

oecd://countries

ISO 3166-1 alpha-3 country codes

oecd://filter-guide

SDMX filter syntax guide

oecd://glossary

Definitions of OECD terms

oecd://llm-instructions

Instructions for AI assistants

oecd://api/info

API information

Prompt Templates

Prompt

Description

analyze_economic_trend

Analyze economic trends over time

compare_countries

Compare data between countries

get_latest_statistics

Get latest statistics

explore_dataset

Guided dataset exploration

find_data_for_question

Find the right dataset for a question

build_filter

Help building SDMX filters

nordic_comparison

Compare Nordic countries


Use Cases

Ekonomer & Forskare

Verktyg:

Verktyg

Beskrivning

query_data

Fråga BNP, inflation, arbetslöshetsdata

search_dataflows

Hitta dataset för forskningsfrågor

get_data_structure

Förstå dataset-dimensioner

Exempel:

  • "Jämför BNP-tillväxt mellan G7-länderna 2020-2024"

  • "Analysera inflationstrender i eurozonen"

  • "Hitta data om arbetsproduktivitet per sektor"

App-exempel: Mobil ekonomisk brief med BNP-trender och jämförelsediagram.


Policyanalytiker

Verktyg:

Verktyg

Beskrivning

get_categories

Bläddra i 17 policyområden

list_dataflows

Hitta relevanta policy-dataset

get_dataflow_url

Generera länkar för rapporter

Exempel:

  • "Vilken sjukvårdsutgiftsdata finns för Sverige?"

  • "Hitta utbildningsresultatindikatorer för PISA-analys"

  • "Jämför miljöpolicyer i nordiska länder"

App-exempel: Hälsostatistik-dashboard med donutdiagram och landjämförelser.


Datajournalister

Verktyg:

Verktyg

Beskrivning

search_indicators

Hitta specifika mätvärden

get_popular_datasets

Få tillgång till ofta citerad data

query_data

Hämta siffror för artiklar

Exempel:

  • "Hämta senaste arbetslöshetssiffror för EU-länder"

  • "Hitta inkomstojämlikhetsdata (Gini-koefficient)"

  • "Jämför skatteintäkter som % av BNP"

App-exempel: Produktivitetsjämförelse med stapeldiagram och trendlinjer.

Economists & Researchers

Tools:

Tool

Description

query_data

Query GDP, inflation, unemployment data

search_dataflows

Find datasets for research questions

get_data_structure

Understand dataset dimensions

Examples:

  • "Compare GDP growth between G7 countries 2020-2024"

  • "Analyze inflation trends in the Eurozone"

  • "Find data on labor productivity by sector"

App Example:

Mobile economic brief with GDP trends, G7 comparison charts, and sparkline visualizations from the QNA dataset.


Policy Analysts

Tools:

Tool

Description

get_categories

Browse 17 policy areas

list_dataflows

Find relevant policy datasets

get_dataflow_url

Generate links for reports

Examples:

  • "What healthcare spending data is available for Sweden?"

  • "Find education outcome indicators for PISA analysis"

  • "Compare environmental policies across Nordic countries"

App Example:

Health statistics dashboard with donut chart overview and country comparison from the HEALTH_STAT dataset.


Data Journalists

Tools:

Tool

Description

search_indicators

Find specific metrics

get_popular_datasets

Access commonly cited data

query_data

Get numbers for stories

Examples:

  • "Get latest unemployment figures for EU countries"

  • "Find income inequality data (Gini coefficient)"

  • "Compare tax revenues as % of GDP"


Data Categories

Category

Code

Description

Datasets

Economy

ECO

GDP, growth, inflation, interest rates

500+

Employment

JOB

Labor market, wages

300+

Trade

TRD

International trade

250+

Health

HEA

Healthcare, life expectancy

200+

Education

EDU

PISA, outcomes

180+

Environment

ENV

Climate, emissions

150+

Innovation

STI

R&D, patents, AI

140+

Energy

NRG

Production, renewables

120+

Taxation

TAX

Tax revenues, tax rates

100+

Finance

FIN

Markets, banking

95+

Government

GOV

Governance, public sector

90+

Social

SOC

Inequality, quality of life

85+

Agriculture

AGR

Production, food security

75+

Industry

IND

Industrial production

70+

Development

DEV

Development aid

60+

Transport

TRA

Infrastructure, mobility

50+

Regional

REG

Subnational data

45+


About

Skapad av: Isak Skogstad

Kontakt: isak.skogstad@me.com

Fristående: Detta projekt är fristående och är inte anslutet till, godkänt av eller officiellt kopplat till OECD (Organisationen för ekonomiskt samarbete och utveckling).

Användarvillkor: Data tillhandahålls via OECD:s öppna SDMX API. Se OECD:s användarvillkor för användningsvillkor.

Created by: Isak Skogstad

Contact: isak.skogstad@me.com

Disclaimer: This project is independent and not affiliated with, endorsed by, or officially connected to the OECD (Organisation for Economic Co-operation and Development).

Terms of use: Data is provided via OECD's open SDMX API. See OECD Terms and Conditions for usage conditions.


Resources


Built with Model Context Protocol SDK | Version 4.0.0

Available Tools

9 tools
get_categoriesA

Get all available OECD data categories (17 categories covering all topics: Economy, Health, Education, Environment, etc.)

Inputs: no named parameters.

get_dataflow_urlA

Generate an OECD Data Explorer URL for a dataset. Use this to provide users with a direct link to explore data visually in their browser.

Inputs: dataflow_id (required), filter.

get_data_structureA

Get the metadata and structure of a specific OECD dataset. Returns dimensions, attributes, and valid values for querying data.

Inputs: dataflow_id (required).

list_categories_detailedA

Get all OECD data categories with example datasets for each category. Returns comprehensive information about all 19 categories.

Inputs: no named parameters.

list_dataflowsA

List available OECD dataflows (datasets), optionally filtered by category. Use this to browse datasets by topic area.

Inputs: category, limit.

query_dataA

Query actual statistical data from an OECD dataset. ⚠️ IMPORTANT: Defaults to last 100 observations (max 1000) to protect context window. Use filters, time periods, or last_n_observations to control data size. Large datasets (e.g. SOCX_AGG) can have 70,000+ observations - always specify limits!

Inputs: dataflow_id (required), filter, start_period, end_period, +1 more.

search_dataflowsA

Search for OECD datasets (dataflows) by keyword. Returns matching datasets with their IDs, names, and descriptions.

Inputs: query (required), limit.

search_indicatorsB

Search for specific economic or social indicators by keyword (e.g., "inflation", "unemployment", "GDP").

Inputs: indicator (required), category.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A3.9/5.0

    Scored across 9 tools

    Disambiguation4/5

    Most tools have distinct purposes, but get_categories and list_categories_detailed overlap in returning category info, though descriptions differentiate by detail level. search_dataflows and list_dataflows both return datasets but use different filters.

    Naming Consistency4/5

    Tools follow a consistent verb_noun pattern (e.g., get_categories, search_dataflows). Minor deviations like list_categories_detailed and get_popular_datasets include adjectives, but overall pattern is clear.

    Tool Count5/5

    9 tools cover the full workflow of browsing, searching, getting metadata, and querying data without being excessive. Each tool serves a clear role.

    Completeness5/5

    The set covers all necessary operations for exploring OECD data: listing/searching datasets, retrieving metadata, querying data, and generating visualization URLs. No obvious gaps for the read-only domain.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

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