How to Use the EuroRates MCP in LlamaIndex
Index live Euro conversion rates directly into your LlamaIndex vector store for grounded financial RAG.
Works with every AI agent you already use
…and any MCP-compatible client
Connect EuroRates MCP to LlamaIndex
Create your Vinkius account to connect EuroRates 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.
Index EuroRates data into LlamaIndex vector stores
Stop letting your financial RAG applications guess exchange values. By calling `get_latest_euro_rates` through this MCP server, you can feed live conversion data directly into your document indexes. The raw rates become searchable nodes in your vector store. This ensures your agent answers financial queries using actual, current exchange numbers. When a user asks about EUR balances, the system pulls the exact rates from the index instead of relying on outdated training data.
Build live financial RAG pipelines
Combine static documents with live exchange rates. Your LlamaIndex query engine can read a PDF invoice in EUR, call `get_latest_euro_rates`, and output the converted total in USD. It bridges the gap between static files and live APIs. The tool execution runs in an isolated V8 sandbox. This keeps your sensitive financial documents separated from external networks while giving your agent the exact numbers it needs to complete the calculation.
Avoid financial hallucinations in agent runs
LLMs are notoriously bad at math and currency rates. By exposing `get_latest_euro_rates` to your LlamaIndex function agent, you force the LLM to fetch real numbers instead of making them up. You can restrict the agent to only use this specific tool for currency tasks. This prevents it from trying to calculate exchange rates manually, keeping your financial reports accurate and auditable.
Set up EuroRates MCP in LlamaIndex
Prerequisites
- Python 3.10+ installed
-
llama-index-tools-mcppackage - 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 providesBasicMCPClientandMcpToolSpec. - 2
Connect with BasicMCPClient
Point
BasicMCPClientto 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 EuroRates MCP tools into nativeFunctionToolobjects that any LlamaIndex agent can use. - 4
Run with any LLM
Create a
FunctionAgentwith the tools and your preferred LLM. SwapOpenAIforAnthropic,Gemini, or any LlamaIndex-supported provider.
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 EuroRates tools.",
)
response = await agent.run("List recent EuroRates data") Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by EuroRates. 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 EuroRates MCP in LlamaIndex
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