Can I check the balance of a specific account using this integration?

Yes! Use the `get_account` tool with the Account ID. Your agent will fetch the latest balance and account metadata directly from Belvo.

How do I list all transactions for a particular connection?

Simply ask the agent to `list_transactions`. You can then inspect specific transaction details using the `get_transaction` tool with the Transaction ID.

Does the integration support all institutions in Brazil and Mexico?

This integration supports all institutions currently active in your Belvo account across supported countries. Use the `list_institutions` tool to see the full list of available banks and platforms.

Belvo MCP Server for CrewAI 12 tools — connect in under 2 minutes

Name: Belvo
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 12 Tools Framework

Connect your CrewAI agents to Belvo through Vinkius, pass the Edge URL in the `mcps` parameter and every Belvo tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Belvo Specialist",
    goal="Help users interact with Belvo effectively",
    backstory=(
        "You are an expert at leveraging Belvo tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Belvo "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 12 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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.

When paired with CrewAI, Belvo becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Belvo tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

Follow these steps to integrate the Belvo MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 12 tools from Belvo

Why Use CrewAI with the Belvo MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Belvo through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Belvo + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Belvo MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Belvo for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Belvo, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Belvo tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Belvo against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Belvo MCP Tools for CrewAI (12)

These 12 tools become available when you connect Belvo to CrewAI 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 CrewAI

Ready-to-use prompts you can give your CrewAI 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 CrewAI

Common issues when connecting Belvo to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Belvo + CrewAI FAQ

Common questions about integrating Belvo MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.