How to Use the REST Countries MCP in LlamaIndex

Index live geography data directly into LlamaIndex for grounded, verifiable knowledge retrieval.

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Connect REST Countries MCP to LlamaIndex

Create your Vinkius account to connect REST Countries to LlamaIndex — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup REST Countries with LlamaIndex

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Ground LlamaIndex in live data

Turn your MCP tool results into a searchable knowledge base. By passing `get_all_countries` output into your index, you ensure your RAG application uses current geography records. This avoids the common trap of relying on static, outdated training data. Your index stays fresh because the tools pull directly from the source during the retrieval phase.

Semantic search with LlamaIndex

Query your geography data using natural language. LlamaIndex maps your questions to the correct tool, such as using `get_country_by_name` when a user asks for specific country details. This makes your data accessible without needing to know the exact API schema. The agent handles the translation from your prompt to the specific tool arguments.

Automated retrieval in LlamaIndex

Set up your agent to fetch data on demand. When a request requires a specific language or currency, the agent triggers `get_countries_by_language` to gather the necessary context. Your index then stores these results for further analysis. This provides a clear audit trail of what data was retrieved and how it influenced the final answer.

Setup guide

Set up REST Countries 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 REST Countries 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 REST Countries tools.",
)
response = await agent.run("List recent REST Countries 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 REST Countries. 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 REST Countries MCP in LlamaIndex

It acts as a live data provider. By indexing the output of these tools, your LlamaIndex application gains immediate access to updated country information.

Absolutely. You can define specific tools as allowed sources, ensuring your LlamaIndex agent only pulls geography data that meets your criteria.

You control the indexing logic. You can choose to store the results in your vector store for future queries or treat them as transient context for a single session.

LlamaIndex manages the asynchronous requests. If a tool call takes time, your agent waits for the response before proceeding, keeping your knowledge base accurate.

The server transmits only the requested record. Your LlamaIndex instance acts as the final gatekeeper for that data, ensuring it remains within your local environment.

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