How to Use the Monnify MCP in Google ADK

Q: How do I instantiate the Monnify MCP Server inside Google ADK?

Import McpToolset from the SDK and pass the server URL. Then, simply add this toolset to your LlmAgent initialization to expose tools like reserveaccount.

Q: Can my Google ADK agent restrict which Monnify tools are exposed?

Yes, you can use the toolnames filter in your McpToolset setup. This prevents the agent from accessing sensitive tools like listdisbursements while keeping query tools active.

Q: How does Google ADK handle high-volume Monnify settlement queries via MCP?

The agent uses listsettlements inside its reasoning loop, taking advantage of Gemini's long-context window to analyze thousands of settlement lines without hitting token limits.

Q: How does my agent find active virtual accounts?

Your agent can call listreservedaccounts to get a paginated list of all active virtual bank accounts. It can then drill down into specific records using getaccountdetails.

Q: Is sensitive settlement and payout data secure during Google ADK MCP operations?

Yes, all settlement records accessed via listsettlements are handled within an isolated, zero-trust network environment. We do not persist payout histories or merchant credentials.

Run Google ADK agents that query Monnify transaction ledgers and trigger disbursements directly from your cloud infrastructure.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Monnify MCP to Google ADK

Create your Vinkius account to connect Monnify to Google ADK 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 Monnify with Google ADK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Sync Monnify Transactions with BigQuery

The `list_transactions` tool extracts complete payment histories directly into your agent's context window. Because Google ADK integrates natively with your cloud data warehouse, your agent can cross-reference these transaction records with historical BigQuery tables in real-time. This lets Gemini analyze massive payment datasets using its million-token context. The agent queries `get_transaction` for any anomalies and flags them instantly for your accounting team.

Automate Disbursements via Google ADK

The `list_disbursements` tool allows your agent to audit outbound bank transfers across your entire Nigerian merchant setup. Using this MCP Server, your Google ADK agent can verify destination routing before any money moves. Before initiating transfers, the agent calls `list_banks` to fetch supported bank codes. This prevents routing failures and keeps your automated payroll or vendor payout loops highly accurate.

Reconcile Invoices with Long-Context Gemini Models

The `list_monnify_invoices` tool pulls active digital invoices directly into your Google ADK runtime. This allows your agent to process hundreds of invoices simultaneously, matching them against incoming settlements. The agent uses `list_settlements` to verify which invoices have cleared. By combining these tools, you build a fully automated reconciliation pipeline that runs entirely on Vertex AI.

Setup guide

Set up Monnify MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Monnify tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Monnify_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Monnify tools via MCP.",
    tools=mcp_tools,
)

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 Monnify. 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 Monnify 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 Monnify MCP in Google ADK

Import `McpToolset` from the SDK and pass the server URL. Then, simply add this toolset to your `LlmAgent` initialization to expose tools like `reserve_account`.

Yes, you can use the `tool_names` filter in your `McpToolset` setup. This prevents the agent from accessing sensitive tools like `list_disbursements` while keeping query tools active.

The agent uses `list_settlements` inside its reasoning loop, taking advantage of Gemini's long-context window to analyze thousands of settlement lines without hitting token limits.

Your agent can call `list_reserved_accounts` to get a paginated list of all active virtual bank accounts. It can then drill down into specific records using `get_account_details`.

Yes, all settlement records accessed via `list_settlements` are handled within an isolated, zero-trust network environment. We do not persist payout histories or merchant credentials.

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