How to Use the Belvo MCP in LlamaIndex

Q: Can LlamaIndex query Belvo investments data?

You can pull portfolio details using the getinvestments tool. The agent indexes the asset breakdown so users can ask questions about their Latin American holdings.

Index Latin American transaction histories from the Belvo MCP Server directly into LlamaIndex for semantic search.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Belvo MCP to LlamaIndex

Create your Vinkius account to connect Belvo 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 Belvo with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Index LatAm financial records via LlamaIndex

Executing `list_transactions` pulls raw banking histories that you immediately dump into a vector store. Users query their spending habits using natural language instead of rigid SQL statements. Semantic search changes how we interact with money. When your agent indexes the output of `list_recurring_expenses`, it understands the context behind monthly subscriptions. Asking about streaming costs pulls exact matches from the indexed API data.

Ground answers in actual account data

Calling `get_account` gives your LlamaIndex application hard facts about current balances and limits. Hallucinations stop when the LLM checks the actual banking API before answering. Combining documents with live endpoints creates smarter RAG pipelines. Your system can cross-reference internal loan policies with live `list_incomes` data fetched through the MCP Server. Decisions happen faster.

Map institutional connections automatically

Running `list_institutions` alongside `list_links` maps out a user's entire financial footprint across Latin America. The index stores these relationships for fast retrieval during complex queries. Finding specific connection details usually requires digging through logs. Hitting `get_link` lets the agent pull exact authentication states and index them. Support teams can ask the agent why a specific bank sync failed.

Setup guide

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

Grab llama-index-tools-mcp via pip. Point BasicMCPClient at your Vinkius URL, wrap it in McpToolSpec, and pass the async tool list to your FunctionAgent.

You can pull portfolio details using the get_investments tool. The agent indexes the asset breakdown so users can ask questions about their Latin American holdings.

Live endpoints bypass the static index. Your LlamaIndex agent calls list_balances in real-time during the query execution to guarantee the numbers are current.

The tool returns the error string directly to the agent. LlamaIndex reads the failure reason and can either retry the request or inform the user.

Vinkius handles the API connection through a zero-trust sandbox. Salary figures and income streams route directly to your vector store without persistent storage on our end.

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