How do I get my Mercury API token?

Log in to your Mercury account at app.mercury.com. Go to **Settings → API Tokens** and click **Create Token**. Choose the token type (Read Only for balance checks, or Read and Write for managing recipients). Copy the token immediately — it will only be shown once. Paste it into the configuration field below, and you're ready. No code, no SDK, no webhooks.

Can my AI agent check my startup's runway instantly during a board meeting?

Absolutely. Just ask your AI agent 'What's my current balance across all Mercury accounts?' and it returns real-time balances for every account — checking, savings, and treasury — in seconds. No tab-switching, no logging in, no waiting for the dashboard to load.

What if I need to review recent transactions for month-end close?

Ask your AI agent to pull transactions from any date range. It retrieves each transaction with amount, counterparty, status, and date — perfect for reconciliation. You can filter by account, ask for Wire vs ACH breakdowns, or request only transactions above a specific threshold, all without exporting CSVs.

Is this suitable for companies with multiple Mercury accounts?

Yes. The integration retrieves data across all accounts linked to your API token — operating accounts, savings accounts, and treasury balances. Perfect for venture-backed startups managing multiple entities, holding companies, or finance teams tracking cash positions across subsidiaries.

Mercury MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Mercury
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Mercury through the Vinkius — pass the Edge URL in the `mcps` parameter and every Mercury 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="Mercury Specialist",
    goal="Help users interact with Mercury effectively",
    backstory=(
        "You are an expert at leveraging Mercury 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 Mercury "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

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

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

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 Mercury MCP Server

Connect your Mercury business banking account to your AI agent and manage your startup finances conversationally.

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

What you can do

Account Balances — Check real-time balances across all your Mercury accounts instantly from your AI agent.
Transaction History — Pull recent transactions filtered by date, amount, or counterparty to track spending patterns.
Recipient Management — List, create, and manage payment recipients for ACH and wire transfers.
Account Details — Retrieve routing numbers, account numbers, and account metadata programmatically.

The Mercury MCP Server exposes 10 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 Mercury to CrewAI via MCP

Follow these steps to integrate the Mercury 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 10 tools from Mercury

Why Use CrewAI with the Mercury MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Mercury 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 the 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

Mercury + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Mercury 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 Mercury, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Mercury 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 Mercury against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Mercury MCP Tools for CrewAI (10)

These 10 tools become available when you connect Mercury to CrewAI via MCP:

create_recipient

Required for sending payments. Create a new payment recipient

get_account

Get bank account details

get_transaction

Get transaction details

get_treasury_balance

Get treasury balance overview

list_accounts

List all Mercury bank accounts

list_payments

List sent payments

list_recipients

List payment recipients

list_statements

List bank statements

list_team_members

List all team members

list_transactions

List recent transactions

Example Prompts for Mercury in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Mercury immediately.

"What's the current balance on all my Mercury accounts?"

"Show me all transactions above $5,000 from this month."

"List all my payment recipients."

Troubleshooting Mercury MCP Server with CrewAI

Common issues when connecting Mercury 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

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

Mercury + CrewAI FAQ

Common questions about integrating Mercury 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.