Global Gender Equality Data

Data

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Available ActionsEach successful request consumes credits as outlined below.

query_gender_data^100cr

Details

Dive into gender equality data for any country in the world. Explore labor force participation gaps, education parity, political representation, legal rights scores, and maternal health outcomes. Compare male and female indicators side by side, track progress over time, and see how countries measure up on gender parity — all from a comprehensive global data set.

Use Cases

Analyze gender gaps in labor force participation, Compare education parity across countries, Research women's political representation, Track maternal health outcomes by region, Evaluate legal rights and Women Business and Law scores, Study economic inclusion and financial access by gender, Monitor progress toward SDG 5 targets, Assess attitudes toward violence against women, Compare male vs female employment rates, Research reproductive health indicators

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STDIO connector for Claude Code, Codex, Cursor, Zed, and other LLMs that require STDIO or custom connections. This lightweight connector routes requests to https://api.agentpmt.com/mcp. All tool execution happens in the cloud and the server cannot edit any files on your computer.

npm install -g @agentpmt/mcp-routeragentpmt-setup

Actions(1)

query_gender_data^100cr4 params(1 required)

Query World Bank gender equality and women's empowerment indicators by country/region and gender aspect. Returns data on labor force participation gaps, education parity indices, political representation, legal framework scores, maternal health, economic empowerment, and attitudes toward violence. Includes automatic gender gap calculations and SDG 5 alignment.

country_or_regionrequiredstring

Country or region name (e.g., 'Rwanda', 'India', 'United States', 'Africa', 'Latin America')

gender_aspectstring

Gender dimension to query: 'labor' (participation, employment), 'education' (literacy, parity indices), 'political' (parliament, ministerial), 'legal' (WBL index), 'health' (maternal mortality, reproductive), 'economic' (financial inclusion, firm ownership), 'violence' (attitudes toward IPV), 'all' (all indicators)

Values:

laboreducationpoliticallegalhealtheconomicviolenceall

Default: all

calculate_gapsboolean

Automatically calculate gender gaps (absolute and percentage differences between male and female indicators)

Default: true

time_periodstring

Time period for data: 'latest', a year like '2020', a range like '2010:2020', or shorthand 'last5'/'last10'

Default: latest

curl -X POST "https://api.agentpmt.com/products/purchase" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer ********" \
  -d '{
    "product_id": "6980e11471cad8f61bf5b1ff",
    "parameters": {
      "action": "query_gender_data",
      "country_or_region": "example_country_or_region",
      "gender_aspect": "all",
      "calculate_gaps": true,
      "time_period": "latest"
    }
  }'

import requests
import json

url = "https://api.agentpmt.com/products/purchase"

headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer ********"
}

data = {
    "product_id": "6980e11471cad8f61bf5b1ff",
    "parameters": {
        "action": "query_gender_data",
        "country_or_region": "example_country_or_region",
        "gender_aspect": "all",
        "calculate_gaps": true,
        "time_period": "latest"
    }
}

response = requests.post(url, headers=headers, json=data)
print(response.status_code)
print(response.json())

const url = "https://api.agentpmt.com/products/purchase";

const headers = {
  "Content-Type": "application/json",
  "Authorization": "Bearer ********"
};

const data = {
  product_id: "6980e11471cad8f61bf5b1ff",
  parameters: {
    "action": "query_gender_data",
    "country_or_region": "example_country_or_region",
    "gender_aspect": "all",
    "calculate_gaps": true,
    "time_period": "latest"
  }
};

fetch(url, {
  method: "POST",
  headers,
  body: JSON.stringify(data)
})
  .then(response => response.json())
  .then(data => console.log(data))
  .catch(error => console.error("Error:", error));

const axios = require('axios');

const url = "https://api.agentpmt.com/products/purchase";

const headers = {
  "Content-Type": "application/json",
  "Authorization": "Bearer ********"
};

const data = {
  product_id: "6980e11471cad8f61bf5b1ff",
  parameters: {
    "action": "query_gender_data",
    "country_or_region": "example_country_or_region",
    "gender_aspect": "all",
    "calculate_gaps": true,
    "time_period": "latest"
  }
};

axios.post(url, data, { headers })
  .then(response => {
    console.log(response.status);
    console.log(response.data);
  })
  .catch(error => {
    console.error("Error:", error.message);
  });

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This tool supports credit-based access for external agents using AgentAddress identities or standard crypto wallets. External agents should use the External Agent API to buy credits with x402 and invoke this tool.

1. Buy Credits

Purchase credits via x402 payment (500 credit minimum, 100 credits = $1).

# Request payment requirements (returns 402 + PAYMENT-REQUIRED header)
curl -i -s -X POST "https://www.agentpmt.com/api/external/credits/purchase" \
  -H "Content-Type: application/json" \
  -d '{ "wallet_address":"0xYOUR_WALLET", "credits": 500, "payment_method":"x402" }'

# Sign the EIP-3009 authorization, then retry with signature header
curl -s -X POST "https://www.agentpmt.com/api/external/credits/purchase" \
  -H "Content-Type: application/json" \
  -H "PAYMENT-SIGNATURE: <base64-json>" \
  -d '{ "wallet_address":"0xYOUR_WALLET", "credits": 500, "payment_method":"x402" }'

2. Create a Session Nonce (nonce used in signed balance/invoke)

curl -s -X POST "https://www.agentpmt.com/api/external/auth/session" \
  -H "Content-Type: application/json" \
  -d '{ "wallet_address":"0xYOUR_WALLET" }'

3. Invoke This Tool

Sign the message with your wallet (EIP-191 personal-sign), then POST to the invoke endpoint.

# Sign this message (wallet MUST be lowercased):
# agentpmt-external
# wallet:0xyourwallet...
# session:<session_nonce>
# request:<request_id>
# method:POST
# path:/external/tools/gender-equality-women-s-empowerment/actions/<actionSlug>/invoke
# payload:<sha256(canonical_json(parameters))>

curl -s -X POST "https://www.agentpmt.com/api/external/tools/gender-equality-women-s-empowerment/actions/<actionSlug>/invoke" \
  -H "Content-Type: application/json" \
  -d '{
    "wallet_address": "0xYOUR_WALLET",
    "session_nonce": "<session_nonce>",
    "request_id": "invoke-uuid",
    "signature": "0x<signature>",
    "parameters": {
      "your_param": "value"
    }
  }'

Usage Instructions

Usage guidance provided directly by the developer for this product.

Gender Equality Data

Overview

Query World Bank gender equality and women's empowerment indicators for any country or region. Access data on labor force participation gaps, education parity indices, political representation, legal framework scores, maternal health, economic empowerment, and attitudes toward violence against women. All indicators are aligned with SDG 5 (Achieve gender equality and empower all women and girls). Data sourced from the World Bank Data360 API and Women, Business and the Law Database.

Actions

query_gender_data

Query gender equality indicators by country/region and gender aspect.

Required Parameters:

Parameter	Type	Description
`action`	string	Must be `"query_gender_data"`
`country_or_region`	string	Country name or region. Examples: `"Rwanda"`, `"India"`, `"United States"`, `"Africa"`, `"Latin America"`

Optional Parameters:

Parameter	Type	Default	Description
`gender_aspect`	string	`"all"`	Specific gender dimension to query. One of: `"labor"`, `"education"`, `"political"`, `"legal"`, `"health"`, `"economic"`, `"violence"`, `"all"`
`calculate_gaps`	boolean	`true`	Automatically calculate gender gaps (male minus female) where male/female pairs exist
`time_period`	string	`"latest"`	Time period for data. Accepts: `"latest"`, a single year like `"2020"`, a range like `"2010:2020"`, or shorthand `"last5"` / `"last10"`

Gender Aspects:

labor -- Female and male labor force participation rates, female-to-male ratio, employment rates by gender
education -- Female and male adult literacy rates, Gender Parity Index (GPI) for primary, secondary, and tertiary education enrollment
political -- Proportion of parliamentary seats held by women (%), proportion of women in ministerial positions (%)
legal -- Women, Business and the Law Index (0-100 scale measuring legal protections and economic opportunities)
health -- Maternal mortality ratio (per 100,000 live births), adolescent fertility rate, contraceptive prevalence, antenatal care coverage, skilled birth attendance
economic -- Financial account ownership by gender (%), female firm ownership (%)
violence -- Attitudes toward intimate partner violence (% of women who believe husband is justified in beating wife)
all -- All available indicators combined

Example: Political representation in Rwanda

{
  "action": "query_gender_data",
  "country_or_region": "Rwanda",
  "gender_aspect": "political",
  "time_period": "latest"
}

Example: Labor force gender gaps in India

{
  "action": "query_gender_data",
  "country_or_region": "India",
  "gender_aspect": "labor",
  "calculate_gaps": true,
  "time_period": "latest"
}

Example: Education parity trends in Sweden

{
  "action": "query_gender_data",
  "country_or_region": "Sweden",
  "gender_aspect": "education",
  "time_period": "2010:2023"
}

Example: Full gender equality profile for Africa

{
  "action": "query_gender_data",
  "country_or_region": "Africa",
  "gender_aspect": "all",
  "time_period": "latest"
}

Example: Maternal health in the United States

{
  "action": "query_gender_data",
  "country_or_region": "United States",
  "gender_aspect": "health",
  "time_period": "latest"
}

Example: Legal framework without gap calculations

{
  "action": "query_gender_data",
  "country_or_region": "Saudi Arabia",
  "gender_aspect": "legal",
  "calculate_gaps": false
}

Example: Economic empowerment for a specific year

{
  "action": "query_gender_data",
  "country_or_region": "Kenya",
  "gender_aspect": "economic",
  "time_period": "2021"
}

Workflows

Comprehensive Gender Equality Report

Call query_gender_data with gender_aspect: "all" and calculate_gaps: true for a full country profile.
The response includes indicators across all dimensions, gender gap calculations, contextual interpretations, and SDG 5 alignment summary.

Cross-Country Comparison

Call query_gender_data for each country with the same gender_aspect and time_period.
Compare gender gaps, interpretation levels (e.g., parliamentary representation thresholds), and indicator values side by side.

Gender Gap Trend Analysis

Call query_gender_data with a time_period range (e.g., "2005:2023") and calculate_gaps: true.
For time-series requests, the response includes year-by-year data points for tracking gap evolution.

SDG 5 Progress Assessment

Call query_gender_data with gender_aspect: "all" to get all SDG 5-aligned indicators.
Review the interpretations against SDG targets (e.g., maternal mortality below 70 per 100,000, parliamentary parity).

Regional Gender Landscape

Call query_gender_data with a region name (e.g., "Africa", "Latin America", "Middle East") and gender_aspect: "all".
The response provides regional aggregate indicators weighted by population.

Notes

Gender gap calculation: When calculate_gaps is true, the tool calculates absolute gap (male - female), percentage gap ((gap / male) * 100), and interpretation: "Near parity" (gap < 1 point), "Male advantage" (male > female), or "Female advantage" (female > male). Gaps are calculated for labor force participation, adult literacy, and financial inclusion.
Gender Parity Index (GPI): For education indicators, GPI values of 0.97-1.03 are interpreted as "Gender parity achieved". Values below 0.97 indicate female disadvantage; above 1.03 indicate female advantage. GPI is reported for primary, secondary, and tertiary enrollment.
Parliamentary representation thresholds: Interpreted as "Gender parity achieved" (>= 50%), "Strong representation" (40-50%), "Approaching critical mass" (30-40%), "Moderate representation" (20-30%), "Low representation" (10-20%), or "Very low representation" (< 10%).
Women, Business and the Law Index: Scored 0-100 (higher is better). Interpreted as "Excellent legal framework" (90-100), "Strong legal protections" (80-90), "Good protections" (70-80), "Moderate protections" (60-70), "Weak protections" (50-60), "Very weak legal framework" (< 50).
Maternal mortality interpretation: "SDG target achieved" (< 70 per 100,000), "Above target but relatively low" (70-140), "Moderate" (140-300), "High" (300-500), "Very high" (> 500). SDG 3.1 target is below 70 per 100,000 live births.
Country input: Accepts common country names (e.g., "United States", "South Korea"), and supports partial matching. Unrecognized countries return a descriptive error.
Supported regions: "World", "Africa", "Asia", "Europe", "Latin America", "Middle East", "North America".
Supported countries: 190+ World Bank member countries including all major economies, African nations, Asian countries, European countries, Latin American countries, and Middle Eastern countries.
SDG 5 alignment: Every response includes an sdg_alignment section referencing SDG 5 and its targets (5.1 through 5.c) on gender equality, violence elimination, and women's empowerment.
time_period validation: Accepts "latest", "last5", "last10", a 4-digit year, or a YYYY:YYYY range. Invalid formats return a validation error.
Concurrency: Indicator fetches are batched concurrently (up to 10 simultaneous API calls) for performance.
Data availability: World Bank data may lag 1-3 years behind the current year. Some indicators are not collected in all countries. Regional aggregates are weighted by population.
Values are rounded to 2 decimal places where applicable.
Data source: World Bank Data360 (World Development Indicators) and Women, Business and the Law Database, updated regularly.