Belvo MCP Server for LlamaIndex 12 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Belvo as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Belvo. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Belvo?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Belvo MCP Server
Connect your Belvo account to any AI agent and orchestrate your financial data workflows across Latin America through natural conversation.
LlamaIndex agents combine Belvo tool responses with indexed documents for comprehensive, grounded answers. Connect 12 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Connection Management — List and inspect all financial institution links (connections) managed by Belvo.
- Account Oversight — Query and retrieve details for banking and gig-economy accounts.
- Transaction Analysis — List and filter financial transactions to understand spending patterns and history.
- Income & Expense Insights — Access processed insights like recurring expenses and income summaries.
- Investment Portfolios — Retrieve detailed information on investment holdings and performance.
- Institution Discovery — List all supported banks and institutions in the Belvo ecosystem.
The Belvo MCP Server exposes 12 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Belvo to LlamaIndex via MCP
Follow these steps to integrate the Belvo MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 12 tools from Belvo
Why Use LlamaIndex with the Belvo MCP Server
LlamaIndex provides unique advantages when paired with Belvo through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Belvo tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Belvo tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Belvo, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Belvo tools were called, what data was returned, and how it influenced the final answer
Belvo + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Belvo MCP Server delivers measurable value.
Hybrid search: combine Belvo real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Belvo to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Belvo for fresh data
Analytical workflows: chain Belvo queries with LlamaIndex's data connectors to build multi-source analytical reports
Belvo MCP Tools for LlamaIndex (12)
These 12 tools become available when you connect Belvo to LlamaIndex via MCP:
get_account
Get specific account details
get_investments
List investment portfolios
get_link
Get specific connection details
get_transaction
Get specific transaction details
list_accounts
List all financial accounts across all links
list_balances
List balances for all accounts
list_incomes
List income insights for the links
list_institutions
List all supported financial institutions
list_links
List all connections (links) to financial institutions
list_owners
List owners of the financial accounts
list_recurring_expenses
List recurring expense insights
list_transactions
List all transactions
Example Prompts for Belvo in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Belvo immediately.
"List all active financial links in my Belvo account."
"Show my account balances across all links."
"List recurring expenses found in my accounts."
Troubleshooting Belvo MCP Server with LlamaIndex
Common issues when connecting Belvo to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpBelvo + LlamaIndex FAQ
Common questions about integrating Belvo MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Belvo with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Belvo to LlamaIndex
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.