How to Use the DeBank (DeFi Wallet Tracker) MCP in Google ADK

Q: How do I configure DeBank (DeFi Wallet Tracker) in Google ADK?

Install google-adk and create an McpToolset using StreamableHttpServerParameters with your Vinkius URL. Pass this toolset into the LlmAgent initialization.

Q: Can Google ADK analyze my DeBank (DeFi Wallet Tracker) transaction history?

The agent uses getuserhistorylist to pull your past trades and transfers. Gemini then processes this historical data to identify trading patterns or calculate tax liabilities.

Q: Does DeBank (DeFi Wallet Tracker) work with Google ADK for token discovery?

Your agent calls listtokensbyids or gettoken to fetch contract addresses, decimals, and current prices. It then formats this data for BigQuery ingestion.

Q: How do I check active networks for a specific wallet?

The getuserusedchainlist tool returns an array of networks where the target address has non-zero balances or past activity.

Connect Google ADK to DeBank to feed multi-chain wallet data into Gemini and cross-reference it with your BigQuery datasets.

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Connect DeBank (DeFi Wallet Tracker) MCP to Google ADK

Create your Vinkius account to connect DeBank (DeFi Wallet Tracker) 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.

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Setup DeBank (DeFi Wallet Tracker) with Google ADK

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Analyze DeFi portfolios with Google ADK

The DeBank MCP Server connects on-chain wallet data to your Gemini-powered enterprise agents. By calling `get_user_history_list` and `get_user_complex_protocol_list`, your agent pulls years of transaction history and active yield positions across multiple chains. Gemini's massive 1M+ token context window easily swallows this raw JSON for deep cross-chain analysis. You initialize the connection using `McpToolset` with the Vinkius URL and pass it to your `LlmAgent`. Once connected, the agent maps the user's active networks via `get_user_used_chain_list` and correlates that activity with internal customer records stored in BigQuery.

Track token holders and history

Enterprise agents need specific market data to build accurate risk models. This MCP integration includes `get_token_top_holders` and `get_token_history_price` to map out asset distribution and volatility. Your agent queries these endpoints and pipelines the results directly into Vertex AI for further processing. You can restrict which tools the agent accesses using the optional `tool_names` filter. If your system only needs basic asset data, you whitelist `get_token` and `list_tokens_by_ids` while blocking the transaction execution endpoints.

Map out decentralized protocols

Understanding where capital flows requires mapping the entire decentralized finance ecosystem. This MCP Server gives your agent the ability to execute `list_all_protocols` and `list_app_protocols` to index active platforms and their supported chains. It then drills down into specific liquidity pools using `get_pool`. Because Vinkius handles the underlying infrastructure, your Google Cloud environment stays clean. You provide the single endpoint token to the HTTP transport, and the server handles all API pagination and rate limits behind the scenes.

Setup guide

Set up DeBank (DeFi Wallet Tracker) 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 DeBank (DeFi Wallet Tracker) 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="DeBank (DeFi Wallet Tracker)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to DeBank (DeFi Wallet Tracker) 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 DeBank. 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.

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Common questions about DeBank (DeFi Wallet Tracker) MCP in Google ADK

Install `google-adk` and create an `McpToolset` using `StreamableHttpServerParameters` with your Vinkius URL. Pass this toolset into the `LlmAgent` initialization.

The agent uses `get_user_history_list` to pull your past trades and transfers. Gemini then processes this historical data to identify trading patterns or calculate tax liabilities.

Your agent calls `list_tokens_by_ids` or `get_token` to fetch contract addresses, decimals, and current prices. It then formats this data for BigQuery ingestion.

The `get_user_used_chain_list` tool returns an array of networks where the target address has non-zero balances or past activity.

Every request routes through a zero-trust Vinkius architecture. The server fetches your specific protocol positions and token allowances, passes the raw data to your agent, and retains absolutely nothing after the HTTP transport closes.

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