How to Use the World Bank Climate & Energy MCP in LlamaIndex

Q: Does the MCP Server support tracking emissions with World Bank Climate & Energy and LlamaIndex?

Yes, calling getco2emissions populates your index. You can then query historical records to see how CO2 levels changed over time relative to other factors.

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Connect World Bank Climate & Energy MCP to LlamaIndex

Create your Vinkius account to connect World Bank Climate & Energy to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup World Bank Climate & Energy with LlamaIndex

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Indexing Climate Data for Retrieval

LlamaIndex doesn't just run the tools; it turns their outputs into searchable facts. When you call `get_co2_emissions`, that metric becomes a document fragment in your index. This means you can query past results and get answers grounded in actual World Bank data, not hallucinations. It lets you build RAG applications where live API measurements are combined with internal documents, making the whole knowledge base verifiable.

Querying Energy Mixes via LlamaIndex

You can combine multiple metrics into a single query. For example, you ask about energy security, and the system retrieves data from both `get_renewable_energy` and `get_electricity_access`. The index pulls together these disparate facts for context. This method allows developers to build unified indices that answer complex questions by synthesizing multiple API calls into one coherent knowledge retrieval session.

Tracking Forest Health with the MCP Server

The World Bank Climate & Energy MCP Server provides metrics on forest cover via `get_forest_area`. By indexing this data, you can ask follow-up questions like: 'Show me all periods where forest area dropped below X% and what the corresponding CO2 emissions were.' This structured approach lets users query historical trends and correlate multiple environmental indicators efficiently.

Setup guide

Set up World Bank Climate & Energy MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all World Bank Climate & Energy MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to World Bank Climate & Energy tools.",
)
response = await agent.run("List recent World Bank Climate & Energy data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by World Bank Open Data. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about World Bank Climate & Energy MCP in LlamaIndex

It indexes the API results into a vector store. This means every metric—like `get_climate_indicator` values—is searchable and retrievable, allowing you to query past sessions for specific answers.

You can combine data points like renewable energy consumption and electricity access into a single index. This lets you run semantic searches across multiple related metrics simultaneously.

Yes, calling `get_co2_emissions` populates your index. You can then query historical records to see how CO2 levels changed over time relative to other factors.

It provides quantitative data on indicators, including forest area percentages and total renewable energy consumption, all accessible via its tools.

This server touches quantitative economic and environmental data (indicators, percentages). The underlying data is aggregated from official sources like the World Bank. You'll need to check your client session management for specific access policies.

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