How to Use the World Bank Full Access MCP in LlamaIndex

Q: How does LlamaIndex use World Bank Full Access?

It indexes the raw output of tools like getgdp and getexternaldebt. When you query, it searches your stored data first, providing answers grounded in historical API calls.

Q: What types of World Bank Full Access indicators can LlamaIndex manage?

The server covers everything from population figures (gettotalpopulation) to economic metrics like getinflation and getlaborforce. Everything gets indexed.

Build knowledge bases with LlamaIndex using World Bank Full Access data.

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Connect World Bank Full Access MCP to LlamaIndex

Create your Vinkius account to connect World Bank Full Access 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 Full Access with LlamaIndex

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Indexing global economic trends

The `get_gdp` tool fetches the Gross Domestic Product, and you can index that raw output into your vector store. This means when you ask a question about regional economic growth, LlamaIndex grounds its answer in actual data points from World Bank Full Access. Want to know how GDP correlates with exports? Querying this indexed knowledge lets you search past results combining `get_exports` and `get_gdp`, rather than just relying on the live tool call.

Semantic search for indicators

Use `search_indicators` to find a specific metric, then index that definition alongside the data retrieved via `get_indicator_data`. This creates highly accurate RAG applications. You can ask about 'poverty' and get results grounded in both the tool output (`get_poverty`) and descriptive documentation. This capability makes your knowledge base robust. Instead of just getting a number, you get context, linking `get_infant_mortality` data to policy summaries.

Analyzing resource investment patterns

LlamaIndex lets you combine diverse inputs into one searchable index. You can fetch both `get_renewable_energy` consumption and `get_research_dev_expenditure`, indexing them together. Your agent then answers complex questions like, 'What is the relationship between renewable energy growth and R&D spending?' This allows you to query configurations across multiple servers while keeping all World Bank Full Access data in a single, cohesive knowledge base.

Setup guide

Set up World Bank Full Access 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 Full Access 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 Full Access tools.",
)
response = await agent.run("List recent World Bank Full Access 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 Full Access MCP in LlamaIndex

It indexes the raw output of tools like `get_gdp` and `get_external_debt`. When you query, it searches your stored data first, providing answers grounded in historical API calls.

The server covers everything from population figures (`get_total_population`) to economic metrics like `get_inflation` and `get_labor_force`. Everything gets indexed.

Yes. You can build a unified index that combines results from multiple indicators, for example, pairing `get_gini_index` with `get_literacy_rate` to give deep context.

It's perfect. The structured nature of the data—like annual GDP growth from `get_gdp_growth`—translates well into verifiable, searchable knowledge chunks.

The server touches economic indicators, including Gross Domestic Product (GDP), total external debt stocks (% of GNI), and population metrics like the total labor force count.

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