How to Use the Asian Development Bank MCP in LlamaIndex

Q: How do I add the Asian Development Bank MCP Server to LlamaIndex?

Install llama-index-tools-mcp and instantiate BasicMCPClient with the Vinkius URL. Wrap it in McpToolSpec and pass it to your agent.

Ground your LlamaIndex knowledge bases in actual Asian Development Bank macroeconomic data instead of training weight guesses.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Asian Development Bank MCP to LlamaIndex

Create your Vinkius account to connect Asian Development Bank 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.

GDPR Free for Subscribers

Setup Asian Development Bank with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Index regional price stability

The `get_inflation_asia` tool pulls consumer price metrics so LlamaIndex can embed them directly into your vector stores. You query the index for Southeast Asian price stability, and the engine retrieves actual percentage changes for Vietnam or Thailand instead of hallucinating numbers. Using `McpToolSpec`, you map the Vinkius endpoint straight into your `FunctionAgent`. The agent pulls the live inflation rates, chunks the numeric data alongside your internal PDFs, and creates a unified index for semantic search.

Embed historical growth metrics

The `get_gdp_asia` tool grabs gross domestic product figures for major economies like PRC and IND. Your LlamaIndex setup stores these historical and current growth metrics as nodes in your graph. This MCP Server integration means your RAG application answers questions based on hard API responses. When a user asks about Japanese economic output, the system queries the live tool, indexes the result, and synthesizes an answer grounded entirely in the retrieved data.

Query dataflows via LlamaIndex MCP Server

The `query_adb_indicators` tool connects your system directly to complex macroeconomic dataflows. You target specific indicators like NGDP_XDC for national accounts or PCPI_PCH for prices using standard economy codes. Your indexing pipeline treats this API endpoint as a dynamic document source. LlamaIndex fetches the trade balances, embeds the numeric relationships, and lets you query past regional configurations with zero manual data entry.

Setup guide

Set up Asian Development Bank 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 Asian Development Bank 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 Asian Development Bank tools.",
)
response = await agent.run("List recent Asian Development Bank data")

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Asian Development Bank. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Asian Development Bank now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Asian Development Bank MCP in LlamaIndex

Install `llama-index-tools-mcp` and instantiate `BasicMCPClient` with the Vinkius URL. Wrap it in `McpToolSpec` and pass it to your agent.

Yes. You index the tool outputs into your vector store. Subsequent semantic searches check your local nodes before hitting the API again.

The MCP protocol provides strict schemas. Your agent reads the descriptions for `query_adb_indicators` and knows exactly which dataflow IDs to pass.

The tools support specific codes including PRC, JPN, IND, KOR, INO, THA, VIE, and PHI. You query these directly through your RAG interface.

The Vinkius endpoint requires a single auth token and operates in a zero-trust sandbox. You fetch public macroeconomic indicators like trade balances, and none of your local vector store documents are exposed to the external API.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript