How to Use the World Bank Countries MCP in LangChain

Q: If I need to know the region for World Bank Countries, how does LangChain handle it?

You use searchregions to list valid geographic areas. The output of this function is designed to be immediately usable as an input parameter for subsequent tool calls in your chain.

Build multi-step reasoning chains for your AI client using the World Bank Countries MCP Server.

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Connect World Bank Countries MCP to LangChain

Create your Vinkius account to connect World Bank Countries to LangChain 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 Countries with LangChain

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Claude

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Building country lists in a chain

The `list_countries` tool gives you the raw list of countries. You can start your agent's workflow by calling this function, and its output becomes the foundational data for subsequent steps. After getting that initial list, you might pass those country codes to another tool—like one checking economic metrics—to filter or augment the results in a multi-step chain.

Filtering by income classification

Use `search_income_levels` when your agent needs to narrow down data. For instance, you can first get a list of all countries via `list_countries`, and then refine that list by passing the desired classifications (like 'HIC') into this function. This allows your ReAct agent to perform structured reasoning: it identifies the goal, calls `search_income_levels` for the filter, and finally uses the resulting subset of countries.

Resolving geographic boundaries

When location is key, start with `search_regions`. This tool establishes the valid geographic areas. You can then combine that knowledge by using a country code obtained from this function to validate against other metadata tools. This sequence of calls—Region -> Country -> Filter—builds robust data pipelines where each output dictates the precise input for the next step in your LangChain agent.

Setup guide

Set up World Bank Countries MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes World Bank Countries tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "world-bank-countries-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent World Bank Countries transactions"
    })
    print(result["messages"][-1].content)

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Common questions about World Bank Countries MCP in LangChain

It lets your AI client build multi-step reasoning pipelines. Instead of getting a single answer, the agent decides which tool to call and in what order—like first checking regions, then filtering countries by income level.

The server provides geographic metadata, including country ISO codes, global income classifications (HIC, LIC), and regional groupings. Your agent uses these structured data points to make its decisions.

You use `search_regions` to list valid geographic areas. The output of this function is designed to be immediately usable as an input parameter for subsequent tool calls in your chain.

It provides structured metadata: country lists, specific income levels (g., HIC, LIC), and recognized geographic regions. These are all discrete inputs for your agent's logic.

This server touches structured metadata: country ISO codes, geographic regions, and global income/lending classifications. Since it deals only in public classification standards, there's no private user data involved.

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