How to Use the EODHD Financial MCP in LlamaIndex

Q: How does LlamaIndex use the EODHD Financial MCP server for RAG?

LlamaIndex treats each tool, like getfundamentals, as a dynamic data source. It calls the tool, gets the financial data, and then indexes that data into a vector store for you to query with natural language.

Index live market data with LlamaIndex to build financial RAG apps that answer questions with real-time facts, not stale data.

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Connect EODHD Financial MCP to LlamaIndex

Create your Vinkius account to connect EODHD Financial 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 EODHD Financial with LlamaIndex

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Turn Market Data into a Knowledge Base

Use `get_fundamentals` and `get_eod_data` to pull company reports and price history. LlamaIndex doesn't just show you the data; it indexes the results into a vector store. Now you can ask questions in natural language like, "What was Apple's P/E ratio last quarter?" and get an answer sourced directly from the indexed results of your previous tool calls. It's a living knowledge base of market data.

Query Across Time and Tickers

Your agent can fetch historical dividends and splits for a whole portfolio using `get_historical_dividends` and `get_historical_splits`. LlamaIndex ingests this structured data automatically. This lets you build query engines that can compare corporate actions across different companies over time. It connects the dots between a stock split and its subsequent price action because the data is indexed and related.

Ground Answers in Real-Time Prices with LlamaIndex

When your RAG application gets a question about current market conditions, it can use `get_realtime_price` or `get_multi_price` to fetch live data. This information is used to synthesize a fresh, up-to-the-minute answer. This avoids stale information. Your LlamaIndex application answers questions based on what the market is doing right now, because the MCP server provides the live tool for it to call on demand.

Setup guide

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

LlamaIndex treats each tool, like `get_fundamentals`, as a dynamic data source. It calls the tool, gets the financial data, and then indexes that data into a vector store for you to query with natural language.

Absolutely. You can build a query engine that uses tools like `search_tickers` and `get_realtime_price` to answer user questions with live, verifiable data straight from the stock market.

You can index anything the tools return. This includes fundamental data, historical prices from `get_eod_data`, dividend history, and stock splits. If a tool returns it, LlamaIndex can index it.

CSVs are static. This MCP server gives your LlamaIndex agent access to live and historical data on demand. It can update its knowledge base automatically by re-running tools like `get_realtime_price`.

The MCP server operates within a zero-trust Vinkius sandbox. It only handles the public financial market data (prices, splits, etc.) you request for specific tickers. Nothing is stored long-term on the server itself.

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