# World Bank Data MCP MCP

> World Bank Education & Health gives your agent immediate access to global statistics on life expectancy, infant mortality rates, literacy levels, and government spending. You can pull precise numbers on health outcomes, education standards, and social welfare indicators across nearly every country without needing any API keys or logins.

## Overview
- **Category:** data-analytics
- **Price:** Free
- **Tags:** social-welfare, life-expectancy, literacy-rates, public-health, education-statistics, humanitarian-data

## Description

This MCP connects your agent directly to massive amounts of humanitarian data from the World Bank. Instead of hunting through academic databases for disparate reports, you ask for a comparison, and you get structured numbers back immediately. You can calculate how much a nation spends on healthcare relative to its GDP, or compare adult literacy rates between continents. This lets you build policy briefs that are backed by hard global metrics.

The real power shows up when you chain this MCP with other data sources. For example, linking education indicators with economic growth data allows your agent to build complex models of development—all within one automated workflow. If you're building an automation across multiple platforms using the Vinkius framework, every tool call gets a cryptographically signed audit trail, meaning you always know exactly where the numbers came from and who called them.

## Tools

### get_life_expectancy
Calculates and returns the expected lifespan at birth for a specified population.

### get_infant_mortality
Provides the rate of infant death for a given time period.

### get_health_expenditure
Gets the current percentage of a country's GDP dedicated to health care spending.

### get_literacy_rate
Determines the percentage of adults who can read and write.

### get_edu_health_indicator
Retrieves any World Bank indicator that measures a combination of education and health data using a specific code.

## Prompt Examples

**Prompt:** 
```
Compare life expectancy in Japan versus the global average.
```

**Response:** 
```
🌍 **Life Expectancy: Japan vs World**

Japan leads globally with a life expectancy of approximately 84 years, well above the worldwide average of ~73 years. This gap reflects Japan's world-class healthcare system and lifestyle factors.
```

**Prompt:** 
```
How has infant mortality improved in India over the last 30 years?
```

**Response:** 
```
🌍 **Infant Mortality: India (1994–2024)**

India has achieved remarkable progress, reducing infant mortality from over 80 per 1,000 live births in the mid-1990s to approximately 25 today — a nearly 70% reduction driven by expanded healthcare access.
```

**Prompt:** 
```
Which countries spend the most on education as a percentage of GDP?
```

**Response:** 
```
🌍 **Education Spending Leaders**

Nordic countries consistently lead: Norway, Sweden, and Denmark each allocate around 6–8% of GDP to education, compared to a global average of approximately 4.3%.
```

## Capabilities

### Calculate Life Expectancy
Retrieve precise life expectancy figures at birth for any country.

### Measure Mortality Rates
Get current data on infant mortality rates to track child health progress.

### Analyze Literacy Standards
Evaluate the global adult literacy rate for policy comparison.

### Track Health Spending
Determine how much a government allocates to healthcare as a percentage of its GDP.

### Compare Indicators
Gather multiple metrics, like education/health indicators, for comparative analysis between nations.

## Use Cases

### Assessing post-conflict recovery
An analyst needs to know if a region is ready for aid. They ask the agent to compare get_infant_mortality rates with current government spending (get_health_expenditure). The agent provides a clear metric of both health risk and financial capacity.

### Writing a policy brief on human capital
A researcher compares three nations. They use get_literacy_rate to establish educational baseline, then compare that to get_life_expectancy to see the total health benefit of their education investment.

### Evaluating a national curriculum change
The agent is tasked with showing the impact of better schooling. It compares pre- and post-intervention data using get_edu_health_indicator, linking it to predicted gains in life expectancy.

### Identifying underfunded health sectors
A policymaker wants to know if a country's spending matches its needs. They check the ratio between required care (implied by get_infant_mortality) and actual allocation using get_health_expenditure.

## Benefits

- Know a country's true development status by comparing its get_life_expectancy against its get_literacy_rate in one query. This gives a holistic picture that isolated data misses.
- Stop guessing about funding needs. Use get_health_expenditure to show exactly how much of the national budget is currently allocated to health care, validating your policy recommendations.
- Track progress over time. By running multiple calls for get_infant_mortality or get_life_expectancy, you can build clear visual evidence of improvement or decline in public health efforts.
- Build multi-layered reports by chaining this MCP with financial tools. You can correlate low literacy rates directly to insufficient spending tracked via get_health_expenditure.
- Eliminate data gaps. Instead of finding one report that combines everything, use the combined power of multiple metrics like get_edu_health_indicator for a single, comprehensive view.

## How It Works

The bottom line is, you get reliable, current global statistics instantly without needing to manually query multiple government sites.

1. Tell your agent exactly what you need—for instance, 'What is the infant mortality rate in Country X?'
2. The MCP executes the request by calling the World Bank data endpoints internally and pulls the correct figures.
3. Your agent receives structured data (the numbers) that it can then write into a report or use for further calculations.

## Frequently Asked Questions

**How do I get started?**
Our World Bank Open Data servers require absolutely zero authentication. You do not need to register, get an API key, or setup webhooks. Just instantly connect and your AI agent can begin querying decades of global data.

**Can it analyze government spending on healthcare?**
Yes, your AI agent can retrieve health expenditure as a % of GDP to correlate spending with life expectancy outcomes over multiple years.

**Can I query literacy improvements over decades?**
Absolutely. Ask your agent to pull education indicators spanning back decades to demonstrate clear upward trends in global literacy.

**What is the scale of the data I can access?**
You have direct access to 64 years of historical data covering 196+ sovereign states and global regional aggregates, powered directly by the World Bank's robust open data initiatives.

**How do I use `get_edu_health_indicator` if my client requires credentials?**
You don't need any keys or passwords; this MCP runs with zero required authentication. Vinkius handles the secure connection, so your agent can pull data directly without you ever entering sensitive details.

**What happens if I use `get_edu_health_indicator` with an invalid code?**
The MCP returns a clear error message specifying the bad code or missing data field. Your agent can catch this structured output and prompt you to check the indicator list, keeping your workflow going.

**Can I use `get_life_expectancy` and `get_infant_mortality` together for a comparison?**
Yes, you can chain these tools to compare outcomes directly. Your agent retrieves both data points—for example, comparing life expectancy against the infant mortality rate—allowing for immediate analysis of public health gaps.

**Is there a limit to what I can query using `get_edu_health_indicator`?**
The tool accepts any standard World Bank education or health indicator code. This means you aren't restricted; if the data exists and has an official identifier, your agent can pull it.