How to Use the TokenTerminal (Crypto Financial Data) MCP in Google ADK

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Connect TokenTerminal (Crypto Financial Data) MCP to Google ADK

Create your Vinkius account to connect TokenTerminal (Crypto Financial Data) 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 TokenTerminal (Crypto Financial Data) with Google ADK

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Querying Market Trends

Need a broad view of market health? The `get_market_metrics` tool gathers aggregated data metrics across the industry. You can run these queries directly from your agent, keeping all analysis within your Google Cloud infrastructure.

Deep Project Analysis

The `get_project_metrics` function lets you pull detailed historical time series data for any project. We're talking revenue, TVL, and active user counts over time. This is ideal when your agents need to act on large datasets already residing in BigQuery.

Identifying Targets

Start by calling `list_projects` if you aren't sure where to look. It gives you a comprehensive list of all crypto projects tracked by Token Terminal. This ensures your agent can target the right asset for analysis.

Setup guide

Set up TokenTerminal (Crypto Financial Data) 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 TokenTerminal (Crypto Financial Data) 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="TokenTerminal (Crypto Financial Data)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to TokenTerminal (Crypto Financial Data) tools via MCP.",
    tools=mcp_tools,
)

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Common questions about TokenTerminal (Crypto Financial Data) MCP in Google ADK

The MCP toolset integrates natively with the Gemini ecosystem and BigQuery. Your agents can use long-context reasoning to analyze complex financial data streams directly from your existing Google Cloud setup.

Yes, you retrieve time series metrics for revenue and TVL. Since the Google ADK supports large context windows, these deep dives won't overload the model, keeping your analysis solid.

It provides institutional-grade crypto financial data. This includes market metrics, project metadata, active user counts, and detailed revenue streams.

The toolset supports Stdio and HTTP transports, making it easy to implement whether you're running in a terminal or integrating into a broader cloud workflow.

Because of the native integration with BigQuery and Vertex AI, your agents stay within the secure perimeter of your existing Google Cloud infrastructure. It's built for enterprise deployment.

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