How to Use the Nansen (Blockchain Analytics) MCP in Google ADK

Q: How do I integrate Nansen (Blockchain Analytics) with Google ADK?

Initialize an McpToolset with your server URL. Pass this object to your LlmAgent tools parameter to grant it access to the full Nansen suite.

Q: Can I restrict which Nansen (Blockchain Analytics) tools my Google ADK agent uses?

Yes. Use the toolnames filter in your McpToolset configuration. This prevents your agent from accessing unnecessary endpoints and keeps your environment clean.

Q: Does Nansen (Blockchain Analytics) support the long-context capabilities of Google ADK?

Yes. You can feed large arrays from profilertransactions into your Gemini models. The 1M+ token context window handles these data-heavy payloads with ease.

Connect Nansen (Blockchain Analytics) to Google ADK to power your Gemini-based enterprise agents with institutional data.

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Connect Nansen (Blockchain Analytics) MCP to Google ADK

Create your Vinkius account to connect Nansen (Blockchain Analytics) 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 Nansen (Blockchain Analytics) with Google ADK

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Enterprise-grade wallet analysis with Google ADK

Use `profiler_premium_labels` to identify institutional entities within your Google Cloud workflows. Your agents can now distinguish between retail wallets and smart money. Integrate `profiler_historical_balances` to track portfolio growth over time. It gives your agents the context they need for long-term risk assessment.

Gemini-powered prediction market insights

Feed `prediction_market_screener` results into your Gemini model for deep reasoning on market sentiment. It helps your agent filter thousands of events in seconds. Get real-time order depth with `prediction_orderbook`. Your agent uses this to spot liquidity gaps, providing a clearer view of market risk than standard UI tools.

Unified flow intelligence for Google Cloud agents

Call `tgm_flows` to visualize capital movement across chains. It bridges the gap between raw blockchain data and your existing BigQuery analytics. Monitor `tgm_indicators` to get automated risk scores for any token. Your agent consumes these scores to adjust its strategy without needing manual data wrangling.

Setup guide

Set up Nansen (Blockchain Analytics) 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 Nansen (Blockchain Analytics) 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="Nansen (Blockchain Analytics)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Nansen (Blockchain Analytics) tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Nansen (Blockchain Analytics) MCP in Google ADK

Initialize an `McpToolset` with your server URL. Pass this object to your `LlmAgent` tools parameter to grant it access to the full Nansen suite.

Yes. Use the `tool_names` filter in your `McpToolset` configuration. This prevents your agent from accessing unnecessary endpoints and keeps your environment clean.

Yes. You can feed large arrays from `profiler_transactions` into your Gemini models. The 1M+ token context window handles these data-heavy payloads with ease.

The server supports both Stdio and HTTP transports. You keep the connection internal to your infrastructure, ensuring only your authorized agents query the data.

The server touches only public blockchain data like transaction history and smart contract interactions. Your internal agent logs remain isolated from the data provider.

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