Climate, Environment, and Land Data Hub

Name: Climate, Environment, and Land Data Hub
Brand: Apoth3osis
SKU: 6980d88a71cad8f61bf5b1b9
Price: 0.10 USD
Availability: InStock

Data

Available ActionsEach successful request consumes credits as outlined below.

query_climate_data^10cr

Details

See how any country's environmental footprint stacks up against the rest of the world. Look up CO2 and greenhouse gas emissions, track how forests and agricultural land are changing, check renewable energy adoption and fossil fuel dependence, and monitor air quality and freshwater use across 100+ countries. Every result includes trend analysis showing whether things are getting better or worse, side-by-side comparisons with global averages, and progress toward Paris Agreement and UN Sustainable Development Goals.

Use Cases

Climate risk analysis,Environmental compliance insights,Pollution trend tracking,Resource and land assessment,Resilience planning

Dynamic MCP Setup

Connect once through AgentPMT Dynamic MCP, then use approved tools from the same agent connection.

30 Second Setup

STDIO connector for Claude Code, Codex, Cursor, Zed, and other LLMs that require STDIO or custom connections.

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

Hosted Streamable HTTPS

MCP endpoint for browser-based apps like ChatGPT, Claude, Grok, or any time you want a streamable connection with no local install.

https://api.agentpmt.com/mcp

Config Example

Use the hosted endpoint directly in clients that support remote MCP. Store your Bearer token in the client config or secret field.

Full connection guide

{
  "mcpServers": {
    "agentpmt": {
      "type": "streamable-http",
      "url": "https://api.agentpmt.com/mcp",
      "headers": {
        "Authorization": "Bearer <AGENTPMT_BEARER_TOKEN>",
        "x-instance-metadata": "{\"client\":\"generic-mcp\",\"platform\":\"remote\"}"
      }
    }
  }
}

Need client videos, organization controls, audit details, and the full feature overview?

More About Dynamic MCP

Actions(1)

query_climate_data^10cr5 params

Fetch climate and environmental data for a country or region from the World Bank. Returns CO2 emissions, greenhouse gas data, forest coverage, renewable energy percentages, air quality (PM2.5), water withdrawals, and electricity access. Includes trend analysis, global comparisons, and Paris Agreement/SDG progress tracking.

country_or_regionstring

Country name in English (e.g., 'Kenya', 'United States', 'China') or 3-letter ISO code (e.g., 'KEN', 'USA'). Defaults to 'World' if omitted.

environmental_topicstring

Environmental topic to query. Options: emissions, forests, water, energy, air_quality, or all.

Values:

emissionsforestswaterenergyair_qualityall

Default: all

time_periodstring

Time period: 'latest' for most recent data, or year range like '2015:2020'.

Default: latest

include_paris_targetsboolean

Include Paris Agreement targets and SDG alignment (SDG 7, 13, 15) in the response.

Default: true

include_per_capitaboolean

Include per capita calculations where applicable. Set to false to exclude per-capita indicators (e.g., CO2 per capita).

Default: true

curl -X POST "https://api.agentpmt.com/products/purchase" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer ********" \
  -d '{
    "product_id": "6980d88a71cad8f61bf5b1b9",
    "parameters": {
      "action": "query_climate_data",
      "environmental_topic": "all",
      "time_period": "latest",
      "include_paris_targets": true,
      "include_per_capita": true
    }
  }'

import requests
import json

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

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

data = {
    "product_id": "6980d88a71cad8f61bf5b1b9",
    "parameters": {
        "action": "query_climate_data",
        "environmental_topic": "all",
        "time_period": "latest",
        "include_paris_targets": true,
        "include_per_capita": true
    }
}

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: "6980d88a71cad8f61bf5b1b9",
  parameters: {
    "action": "query_climate_data",
    "environmental_topic": "all",
    "time_period": "latest",
    "include_paris_targets": true,
    "include_per_capita": true
  }
};

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: "6980d88a71cad8f61bf5b1b9",
  parameters: {
    "action": "query_climate_data",
    "environmental_topic": "all",
    "time_period": "latest",
    "include_paris_targets": true,
    "include_per_capita": true
  }
};

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

Login to view your API and budget keys. The example above uses placeholder values. Sign in to see personalized code with your bearer token.

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.

Recommended

Credit-Based Access Using AgentAddress

AgentAddress is preferred when an autonomous agent needs persistent file access, stored platform state, or maximum tool use ability across repeated calls.

Open Credit-Based Access Using AgentAddress

Direct x402 Payment

Use direct x402 for independent one-off tool calls that do not require shared files or stored platform state.

Accepted public payments

Stablecoin: USDC
Chains: Base, Arbitrum, Optimism, Polygon, and Avalanche

Direct x402 payments are not enabled for this product; use AgentAddress credit access instead.

Product Skill Package

This product has a published Agent Skill package. Install it when an autonomous agent needs product-specific operating instructions in its local skill registry.

Download SKILL.md View package source OpenClaw listing

OpenClaw install

skills.sh install

Usage Instructions

Usage guidance provided directly by the developer for this product.

Climate, Environment, and Land Data Hub

Overview

Natural language interface to World Bank climate and environmental data. Query CO2 emissions, forest coverage, water resources, energy consumption, and air quality by country or region. Supports 100+ countries by English name. No indicator codes needed -- just provide a country name and topic.

Data sourced from the World Bank API. Covers emissions (CO2, GHG, methane, nitrous oxide), forests and land use, energy access and renewables, water resources, and air quality (PM2.5 exposure). Includes Paris Agreement targets, SDG alignment (SDG 7, 13, 15), trend analysis, and global comparisons.

Actions

query_climate_data

Fetches climate and environmental data for a country or region from the World Bank.

Required parameters: None (all optional; defaults to World/all topics/latest).

Optional parameters:

country_or_region (string): Country name in English (e.g., "Kenya", "United States", "China") or 3-letter ISO code (e.g., "KEN", "USA"). Defaults to "World" if omitted. Unrecognized names return an error with a suggestion.
environmental_topic (string): One of "emissions", "forests", "water", "energy", "air_quality", or "all". Defaults to "all".
time_period (string): "latest" for most recent data, or a year range like "2015:2020". Defaults to "latest".
include_paris_targets (boolean): Include Paris Agreement targets and SDG alignment in the response. Defaults to true.
include_per_capita (boolean): Include per capita calculations where applicable. Defaults to true. Set to false to exclude per-capita indicators (e.g., CO2 per capita).

Example -- Get emissions data for Kenya:

{
  "action": "query_climate_data",
  "country_or_region": "Kenya",
  "environmental_topic": "emissions"
}

Example -- Get all climate data for Brazil with a time range:

{
  "action": "query_climate_data",
  "country_or_region": "Brazil",
  "time_period": "2015:2020"
}

Example -- Forest data for the world, no per-capita:

{
  "action": "query_climate_data",
  "environmental_topic": "forests",
  "include_per_capita": false
}

Example -- Energy data for Sub-Saharan Africa without Paris targets:

{
  "action": "query_climate_data",
  "country_or_region": "Sub-Saharan Africa",
  "environmental_topic": "energy",
  "include_paris_targets": false
}

Example -- Air quality for India:

{
  "action": "query_climate_data",
  "country_or_region": "India",
  "environmental_topic": "air_quality"
}

Workflows

Country Climate Profile

Call query_climate_data with a country and environmental_topic: "all" to get a full climate profile.
Review the paris_agreement_targets and sdg_alignment sections for policy context.
Check the global_comparison on each indicator to see how the country compares to the world average.

Emissions Tracking Over Time

Call query_climate_data with environmental_topic: "emissions" and a time_period range (e.g., "2010:2022").
Review the trend field on each indicator to see if emissions are increasing, decreasing, or stable.

Regional Comparison

Call query_climate_data for a region (e.g., "Sub-Saharan Africa", "Latin America", "South Asia").
Compare with a specific country by calling again with that country name.
Use the global_comparison data to contextualize results.

Notes

Supported countries: 100+ countries by full English name (e.g., "Kenya", "Germany", "Brazil"), plus World Bank regions ("Sub-Saharan Africa", "Latin America", "East Asia and Pacific", "Europe and Central Asia", "Middle East and North Africa", "North America", "South Asia") and income groups ("Low Income", "Lower Middle Income", "Upper Middle Income", "High Income").
3-letter ISO codes are also accepted (e.g., "KEN", "USA", "CHN"). 2-letter codes are accepted if uppercase.
Country names must be in English. Native-language or Unicode names are not supported.
Country name input longer than 100 characters is rejected.
If country_or_region is omitted or empty, it defaults to "World" (WLD).
If environmental_topic is omitted or not recognized, it defaults to "all" (returns all indicators).
Environmental topics and their indicators:
- emissions: CO2 total, CO2 per capita, total GHG, methane
- forests: forest area %, forest area sq km, agricultural land %
- water: freshwater withdrawal, clean fuel access
- energy: renewable energy %, fossil fuel %, renewable electricity %, access to electricity %
- air_quality: PM2.5 exposure, clean fuel access
Setting include_per_capita to false filters out any indicator key containing "per_capita".
Response includes: data values with year, trend analysis (increasing/decreasing/stable over ~10 years), global comparison (percentage above/below world average), Paris Agreement targets, SDG alignment, and a summary with data availability percentage.
When no data is found for any indicator, success is false and a message is included.
Data availability varies by country and indicator. Some indicators may return null values.

Frequently Asked Questions

How do I connect this tool to an external agent?

You can install the local MCP server by opening a terminal and running:

Install commands

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:

Hosted MCP config

{
  "mcpServers": {
    "agentpmt": {
      "type": "streamable-http",
      "url": "https://api.agentpmt.com/mcp",
      "headers": {
        "Authorization": "Bearer <AGENTPMT_BEARER_TOKEN>",
        "x-instance-metadata": "{\"client\":\"generic-mcp\",\"platform\":\"remote\"}"
      }
    }
  }
}

View MCP Connection Instructions for more details.

How does an external agent use this tool?

After the external agent is connected to an Agent Group that can use this tool, paste this prompt into the agent:

Agent prompt

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 6980d88a71cad8f61bf5b1b9 ("Climate, Environment, and Land Data Hub"). 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.

Climate, Environment, and Land Data Hub

Available ActionsEach successful request consumes credits as outlined below.

Details

Use Cases

Dynamic MCP Setup

30 Second Setup

Hosted Streamable HTTPS

Config Example

Actions(1)

Credit-Based Access Using AgentAddress

Direct x402 Payment

Product Skill Package

Usage Instructions

Climate, Environment, and Land Data Hub

Overview

Actions

query_climate_data

Workflows

Country Climate Profile

Emissions Tracking Over Time

Regional Comparison

Notes

Frequently Asked Questions

How do I connect this tool to an external agent?

How does an external agent use this tool?

Articles and media

Energy and Artificial Intelligence: The New Grid Bargain

How AI Affects the Environment: Water, Labor, and Local Trust

Artificial Intelligence for Agriculture Needs Readable Data

Looking for help integrating AI into your business? Set up a free consultation.

Climate, Environment, and Land Data Hub

Available ActionsEach successful request consumes credits as outlined below.

Details

Use Cases

Dynamic MCP Setup

30 Second Setup

Hosted Streamable HTTPS

Config Example

Frequently Asked Questions

How do I connect this tool to an external agent?

How does an external agent use this tool?

Related resources

Articles and media

Energy and Artificial Intelligence: The New Grid Bargain

How AI Affects the Environment: Water, Labor, and Local Trust

Artificial Intelligence for Agriculture Needs Readable Data

Looking for help integrating AI into your business? Set up a free consultation.