# Global Agriculture & Food Security Data ## Links - Product page URL: https://www.agentpmt.com/marketplace/agriculture-food-security - Product markdown URL: https://www.agentpmt.com/marketplace/agriculture-food-security?format=agent-md - Product JSON URL: https://www.agentpmt.com/marketplace/agriculture-food-security?format=agent-json ## Overview - Product ID: 6980decb71cad8f61bf5b1f1 - Type: data - Unit type: request - Price: 500 credits - Categories: Data Science, Data Processing, Academic & Scientific Research, Public Records & Government Data, Environmental & Climate Data, Civic Data & Demographics, Recipe & Nutrition - Generated at: 2026-07-05T12:17:34.833Z ### Page Description Explore agriculture and food security data for any country in the world. Look up crop yields, undernourishment rates, agricultural productivity, land use patterns, and rural development indicators. Compare food security outcomes across countries, track trends in agricultural output, and assess progress toward ending hunger — all from a comprehensive global data set. ### Agent Description Query agricultural production, food security, malnutrition, land use, and productivity indicators for any country or region. Get cereal yields, undernourishment prevalence, agricultural value added, and rural population context. Supports trend analysis, regional comparisons, and SDG 2 alignment. ## Details ### Details Explore agriculture and food security data for any country in the world. Look up crop yields, undernourishment rates, agricultural productivity, land use patterns, and rural development indicators. Compare food security outcomes across countries, track trends in agricultural output, and assess progress toward ending hunger — all from a comprehensive global data set. ### Actions - `query_agriculture_data` (5 credits): Fetch agricultural and food security indicator data for a country or region, including crop yields, undernourishment rates, land use, productivity metrics, and rural development context. ### Use Cases Research food security levels by country, Track crop yield trends over time, Analyze agricultural productivity across regions, Study undernourishment and malnutrition rates, Compare land use patterns between countries, Monitor rural population and agricultural employment, Assess progress toward SDG 2 zero hunger targets, Research agricultural value added as percentage of GDP, Evaluate food production capacity by region, Support policy research on rural development ### Workflows Using This Tool No public workflows currently reference this product. ### Related Content No related content is currently linked to this product. ## Integration Details ### DynamicMCP - Setup page URL: https://www.agentpmt.com/dynamic-mcp - Claude setup guide: https://www.agentpmt.com/dynamic-mcp#platform=claude - ChatGPT setup guide: https://www.agentpmt.com/dynamic-mcp#platform=chatgpt - Cursor setup guide: https://www.agentpmt.com/dynamic-mcp#platform=cursor - Windsurf setup guide: https://www.agentpmt.com/dynamic-mcp#platform=windsurf Use the local router for command-based MCP clients. It forwards requests to `https://api.agentpmt.com/mcp` and does not execute tools locally. ```bash npm install -g @agentpmt/mcp-router agentpmt-setup ``` ### REST API The live page renders cURL, Python, JavaScript, and Node.js examples. Logged-in users see those examples prefilled with their own API and budget credentials. - Purchase endpoint: https://api.agentpmt.com/products/purchase - Authorization format: `Bearer ` ```bash curl -X POST "https://api.agentpmt.com/products/purchase" \ -H "Content-Type: application/json" \ -H "Authorization: Bearer eW91ci1hcGkta2V5LWhlcmU6eW91ci1idWRnZXQta2V5LWhlcmU=" \ -d '{ "product_id": "6980decb71cad8f61bf5b1f1", "parameters": { "action": "query_agriculture_data", "country_or_region": "example_country_or_region", "agriculture_topic": "all", "time_period": "latest", "include_rural_context": true, "include_regional_comparison": true, "include_trends": true } }' ``` ### Autonomous Agents Autonomous agents can access this tool through AgentAddress credit balances or direct x402 payments. Use the Autonomous Agent API reference for endpoint shapes after choosing the access pattern below. - Autonomous Agent API reference URL: https://www.agentpmt.com/docs/api-reference/autonomous-agents - Autonomous Agent API reference markdown URL: https://www.agentpmt.com/docs/api-reference/autonomous-agents?format=agent-md - Credit-Based Access Using AgentAddress: https://www.agentpmt.com/docs/autonomous-agents/credit-based-tool-usage-with-agentaddress - AgentAddress is preferred for persistent file access, stored platform state, and maximum tool use ability across repeated calls. - Direct x402 is for independent one-off tool calls that do not require shared files or stored platform state. - Direct x402 public payments: USDC on Base, Arbitrum, Optimism, Polygon, and Avalanche. #### Product Skill Package This product has a published Agent Skill package for product-specific operating instructions. - Skill slug: global-agriculture-food-security-data - Version: 1.0.0 - Download SKILL.md: https://raw.githubusercontent.com/AgentPMT/agent-skills/main/skills/global-agriculture-food-security-data/SKILL.md - Package source: https://github.com/AgentPMT/agent-skills/tree/main/skills/global-agriculture-food-security-data - OpenClaw listing: https://clawhub.ai/agentpmt/global-agriculture-food-security-data - OpenClaw install: `openclaw skills install global-agriculture-food-security-data` - skills.sh install: `npx skills add AgentPMT/agent-skills --skill global-agriculture-food-security-data` - Last published: 2026-06-24T05:37:55.790Z ### Schema #### Parameters - Schema type: actions ```json { "actions": { "query_agriculture_data": { "description": "Fetch agricultural and food security indicator data for a country or region, including crop yields, undernourishment rates, land use, productivity metrics, and rural development context.", "properties": { "country_or_region": { "type": "string", "description": "Country or region name in plain language (e.g., 'India', 'Sub-Saharan Africa', 'Brazil', 'World')", "required": true }, "agriculture_topic": { "type": "string", "description": "Topic filter: 'production', 'food_security', 'malnutrition', 'land_use', 'productivity', or 'all'", "required": false, "default": "all", "enum": [ "production", "food_security", "malnutrition", "land_use", "productivity", "all" ] }, "time_period": { "type": "string", "description": "Time period: 'latest', 'last_5_years', 'last_10_years', 'YYYY:YYYY' range, or single 'YYYY' year", "required": false, "default": "latest" }, "include_rural_context": { "type": "boolean", "description": "Include rural population percentage and agricultural employment data for additional context", "required": false, "default": true }, "include_regional_comparison": { "type": "boolean", "description": "Include comparison data from World, Sub-Saharan Africa, South Asia, Latin America, East Asia, and Middle East", "required": false, "default": true }, "include_trends": { "type": "boolean", "description": "Include trend analysis with change direction (improving/worsening/stable) when historical data is available", "required": false, "default": true } } } }, "properties": { "action": { "type": "string", "description": "Action to perform: 'get_instructions' for documentation, 'query_agriculture_data' to fetch data", "required": true, "enum": [ "get_instructions", "query_agriculture_data" ] }, "country_or_region": { "type": "string", "description": "Country or region name in plain language (e.g., 'India', 'Sub-Saharan Africa', 'Brazil', 'World')", "required": false }, "agriculture_topic": { "type": "string", "description": "Topic: 'production', 'food_security', 'malnutrition', 'land_use', 'productivity', or 'all'", "required": false, "default": "all" }, "time_period": { "type": "string", "description": "Time period: 'latest' (most recent), 'last_10_years', 'last_5_years', or specific range 'YYYY:YYYY' (e.g., '2015:2020')", "required": false, "default": "latest" }, "include_rural_context": { "type": "boolean", "description": "Include rural population and agricultural employment context", "required": false, "default": true }, "include_regional_comparison": { "type": "boolean", "description": "Include regional/global comparison data for context", "required": false, "default": true }, "include_trends": { "type": "boolean", "description": "Include trend analysis if historical data available", "required": false, "default": true } } } ``` ### Usage Instructions # Agriculture & Food Security Data Access comprehensive agricultural statistics and food security indicators from the World Bank's World Development Indicators database through a natural language interface. ## Overview This tool provides natural language access to World Bank agricultural data covering crop production, food security, land use, productivity metrics, and economic context. It supports 200+ countries and regional aggregations, with built-in trend analysis, regional comparisons, and SDG 2 (Zero Hunger) alignment tracking. Data is sourced from the World Bank World Development Indicators and FAO databases. ## Actions ### query_agriculture_data Query agricultural and food security indicators for any country or region. #### Required Parameters - **action** (string): Must be `"query_agriculture_data"` - **country_or_region** (string): Country or region name in plain language - Country names: `"India"`, `"Brazil"`, `"Kenya"`, `"United States"` - Regions: `"Sub-Saharan Africa"`, `"Latin America"`, `"South Asia"`, `"East Asia"`, `"Middle East"` - Global: `"World"` or `"Global"` - Income groups: `"Low Income"`, `"Lower Middle Income"`, `"Upper Middle Income"`, `"High Income"` - ISO3 codes also accepted: `"USA"`, `"IND"`, `"KEN"` #### Optional Parameters - **agriculture_topic** (string, default: `"all"`): Topic filter for indicators - `"production"` - Cereal yield, crop production index, livestock production index, food production index - `"food_security"` - Undernourishment prevalence, food deficit, food production index, cereal import dependency - `"malnutrition"` - Undernourishment prevalence, food deficit (caloric deficits) - `"land_use"` - Agricultural land, arable land, arable land per person, forest area, irrigated land - `"productivity"` - Cereal yield, fertilizer consumption, agricultural machinery, agriculture value added growth - `"all"` - All available agricultural indicators (20 indicators) - **time_period** (string, default: `"latest"`): Time period for data retrieval - `"latest"` - Most recent available data point - `"last_5_years"` - Last 5 years of data - `"last_10_years"` - Last 10 years of data - `"YYYY:YYYY"` - Specific year range (e.g., `"2015:2020"`), years must be between 1960 and current year - `"YYYY"` - Single specific year (e.g., `"2020"`) - **include_rural_context** (boolean, default: `true`): Include rural population percentage and agricultural employment data for additional context - **include_regional_comparison** (boolean, default: `true`): Include comparison data from World, Sub-Saharan Africa, South Asia, Latin America & Caribbean, East Asia & Pacific, and Middle East & North Africa - **include_trends** (boolean, default: `true`): Include trend analysis with absolute and percentage change, direction assessment (improving/worsening/stable), when historical data is available #### Example: Latest data for a country ```json { "action": "query_agriculture_data", "country_or_region": "India", "agriculture_topic": "all", "time_period": "latest" } ``` #### Example: Food security trends over time ```json { "action": "query_agriculture_data", "country_or_region": "Kenya", "agriculture_topic": "food_security", "time_period": "last_10_years", "include_trends": true } ``` #### Example: Regional productivity analysis ```json { "action": "query_agriculture_data", "country_or_region": "Sub-Saharan Africa", "agriculture_topic": "productivity", "time_period": "last_5_years" } ``` #### Example: Land use with minimal extras ```json { "action": "query_agriculture_data", "country_or_region": "Brazil", "agriculture_topic": "land_use", "time_period": "2010:2020", "include_rural_context": false, "include_regional_comparison": false } ``` #### Example: Malnutrition data for income group ```json { "action": "query_agriculture_data", "country_or_region": "Low Income", "agriculture_topic": "malnutrition", "time_period": "latest" } ``` ## Response Structure Responses include: - **data**: Indicator values with human-readable names, latest values, years, units, country name, and source attribution - **productivity_metrics**: Derived metrics including cereal productivity assessment (Low/Moderate/Good/High with recommendations), agricultural efficiency ratio (GDP share vs employment share), and land productivity context - **rural_context**: Rural population percentage and agricultural employment share (when `include_rural_context` is true) - **trends**: For each indicator with historical data: oldest/newest values and years, absolute and percentage change, direction (improving/worsening/stable), and data point count - **regional_comparison**: Comparison values from 6 major regions (when `include_regional_comparison` is true) - **insights**: Human-readable analytical insights based on data values, trends, and regional comparisons - **sdg_alignment**: SDG 2 Zero Hunger alignment information - **data_notes**: Context notes about methodology and data quality ## Key Indicators Reference | Indicator | Unit | Description | |-----------|------|-------------| | cereal_yield | kg per hectare | Cereal productivity (global avg ~4,000) | | crop_production_index | index (2014-2016=100) | Overall crop production level | | livestock_production_index | index (2014-2016=100) | Livestock production level | | agricultural_land | % of land area | Land used for agriculture | | arable_land | % of land area | Land suitable for crops | | arable_land_per_person | hectares per person | Per capita arable land | | forest_area | % of land area | Forest coverage | | irrigated_land | % of agricultural land | Irrigated portion of farmland | | undernourishment_prevalence | % of population | Population unable to acquire enough food | | food_production_index | index (2014-2016=100) | Overall food production level | | food_deficit | kcal/person/day | Depth of caloric food deficit | | fertilizer_consumption | kg/ha of arable land | Fertilizer use intensity | | agricultural_machinery | number of tractors | Mechanization level | | agricultural_methane | % of total emissions | Agriculture's methane contribution | | agriculture_value_added | % of GDP | Agriculture's share of economy | | agriculture_value_added_growth | annual % growth | Agriculture GDP growth rate | | employment_agriculture | % of total employment | Agricultural workforce share | | rural_population | % of total population | Rural population share | | cereal_import_dependency | % | Reliance on cereal imports | ## Productivity Assessments Cereal yield classifications used in productivity_metrics: - **Low productivity**: Below 2,000 kg/ha - significant improvement potential - **Moderate productivity**: 2,000-4,000 kg/ha - room for improvement - **Good productivity**: 4,000-6,000 kg/ha - above average - **High productivity**: Above 6,000 kg/ha - excellent yields ## Workflows 1. **Country Agricultural Profile**: Query with `agriculture_topic: "all"` and `time_period: "latest"` to get a comprehensive snapshot of a country's agricultural sector 2. **Food Security Monitoring**: Query `agriculture_topic: "food_security"` with `time_period: "last_10_years"` and `include_trends: true` to track food security progress 3. **Cross-Country Comparison**: Run separate queries for multiple countries with `include_regional_comparison: true` to compare against regional benchmarks 4. **Productivity Gap Analysis**: Query `agriculture_topic: "productivity"` to get yield assessments and efficiency ratios with recommendations ## Notes - Data sourced from World Bank World Development Indicators and FAO - Most recent data is typically 1-3 years behind current year due to collection/processing delays - Data availability varies by country and indicator; some countries may have gaps - Production indices use 2014-2016 as the base period (value of 100) - Cereal yield is based on harvested area, not planted area - Undernourishment is based on minimum dietary energy requirements - When a country name is not recognized, a descriptive error is returned with guidance - If no country_or_region is provided, returns an error requesting the parameter - The tool supports partial name matching for country lookups (e.g., "korea" matches "south korea") - Trend direction for undernourishment and food deficit is inverted (decrease = improving) - Regional comparison fetches the top 5 key indicators (not all) for performance reasons ## Pricing $0.05 per request ### Frequently Asked Questions #### How do I connect this tool to an external agent? - Page URL: https://www.agentpmt.com/faq - Markdown URL: https://www.agentpmt.com/faq?format=agent-md You can install the local MCP server by opening a terminal and running: ``` npm install -g @agentpmt/mcp-router agentpmt-setup ``` This will connect you to local agents like Claude Code, Windsurf, Grok Build, Cursor, etc. Alternatively you can connect to the hosted version with this config block, no installation required: ``` { "mcpServers": { "agentpmt": { "type": "streamable-http", "url": "https://api.agentpmt.com/mcp", "headers": { "Authorization": "Bearer ", "x-instance-metadata": "{\"client\":\"generic-mcp\",\"platform\":\"remote\"}" } } } } ``` [View MCP Connection Instructions](/docs/mcp-reference/connection) for more details. #### How does an external agent use this tool? - Page URL: https://www.agentpmt.com/faq - Markdown URL: https://www.agentpmt.com/faq?format=agent-md After the external agent is connected to an Agent Group that can use this tool, paste this prompt into the agent: > Use the AgentPMT-Tool-Search-and-Execution tool. First call action 'get\_instructions' so you know how to use the tool search interface. Then call action 'get\_schema' with tool\_id 6980decb71cad8f61bf5b1f1 ("Global Agriculture & Food Security Data"). After reading the schema and any returned instructions, tell me what this tool can do, we are going to be using it The agent should fetch the tool schema first, collect the required parameters for your request, and then call the tool through AgentPMT. ### Dependencies This product has no public dependency products.