How to Use the Dune Analytics (Web3 SQL Analytics API) MCP in Google ADK

Q: Can Google ADK agents run Dune Analytics (Web3 SQL Analytics API) queries in parallel?

Yes. Your agent can trigger multiple runs via executequery and track them concurrently. Google ADK manages the tool calls while Dune handles the heavy database lifting.

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Connect Dune Analytics (Web3 SQL Analytics API) MCP to Google ADK

Create your Vinkius account to connect Dune Analytics (Web3 SQL Analytics API) 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 Dune Analytics (Web3 SQL Analytics API) with Google ADK

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Run heavy Web3 SQL queries inside Google ADK

The `execute_query` tool starts a SQL run on Dune's engines directly from your Google ADK agent. By executing this, your agent initiates SQL queries on Dune's engines, receiving a tracking ID instantly. This setup lets Gemini models process massive blockchain datasets. You can feed raw SQL outputs into your Google ADK workspace alongside your existing BigQuery data.

Monitor execution states using Gemini's long context

The `get_execution_status` tool monitors whether your blockchain query is pending, completed, or failed. Checking this status keeps your agent informed without hanging the main thread. Because Gemini handles huge token windows, you can pass large execution histories to the model. The agent uses this MCP server to decide when to fetch the final dataset.

Fetch results and cancel slow database tasks

The `get_execution_results` tool retrieves the raw database rows once your query finishes executing. This feeds live Web3 metrics directly into your enterprise analytics pipeline. This MCP server keeps your Google ADK agent from wasting resources on runaway database operations. If a query gets stuck or costs too much, the agent calls `cancel_execution` to stop it.

Setup guide

Set up Dune Analytics (Web3 SQL Analytics API) 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 Dune Analytics (Web3 SQL Analytics API) 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="Dune Analytics (Web3 SQL Analytics API)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Dune Analytics (Web3 SQL Analytics API) tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Dune Analytics (Web3 SQL Analytics API) MCP in Google ADK

Initialize the toolset using the server URL in your Python environment. Pass this toolset to your LlmAgent constructor so your Gemini models can access the Dune SQL tools.

Yes. Your agent can trigger multiple runs via `execute_query` and track them concurrently. Google ADK manages the tool calls while Dune handles the heavy database lifting.

The server passes Dune's native responses directly to Google ADK. Your agent can read the status via `get_execution_status` to space out requests and avoid hitting API limits.

Yes. Google ADK supports a tool name filter. You can restrict the MCP tools to only use `get_execution_results` if you want to prevent it from running new expensive queries.

Absolutely. Vinkius uses ephemeral, zero-trust V8 isolates to run the code. Your SQL query text and blockchain results flow directly to your Google ADK client without persistent storage.

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