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How to Use the Mnemonic MCP in Google ADK

Connect Mnemonic to Google ADK to run long-context NFT intelligence directly inside your BigQuery-backed enterprise agents.

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Google ADK

Connect Mnemonic MCP to Google ADK

Create your Vinkius account to connect Mnemonic 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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Deep NFT intelligence for Google ADK

Integrate `get_wallet_history` and `get_nft_owners` to give your agent a granular view of asset movement. This helps when you need to reconcile wallet activity against your existing BigQuery datasets. The server feeds structured data into your Gemini models. It allows for complex reasoning over large token sets without losing precision.

Enterprise-grade collection insights

Use `get_collection_distribution` to map out ownership patterns for your internal reports. Your agent can now query this MCP Server to validate asset concentration in real-time. It bridges the gap between your cloud infrastructure and raw chain data. You get the insights without managing separate indexing pipelines.

Standardized toolset architecture

Define your `McpToolset` to expose only the relevant functions like `list_collection_tokens`. This keeps your agent's focus sharp and your tool execution predictable. Google ADK handles the transport, while this server handles the data retrieval. It turns your agent into a powerful research engine for NFT markets.

Setup guide

Set up Mnemonic 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. 1

    Install Google ADK

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

  2. 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. 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. 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 Mnemonic 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="Mnemonic_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Mnemonic tools via MCP.",
    tools=mcp_tools,
)

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Mnemonic. 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 Mnemonic MCP in Google ADK

You register the server URL in your `McpToolset` configuration. The agent then dynamically accesses the 12 available tools to fetch data on demand.
Mnemonic provides public chain data. Your private data remains in your infrastructure, and the agent uses this server only for external market context.
You operate within standard API rate limits. The integration is designed to handle high-frequency requests required for enterprise-level agents.
Use the tool_names parameter in your configuration. This restricts the agent to only the specific Mnemonic functions you need.
Data is fetched over encrypted channels. We ensure that only authorized wallet queries reach the chain indexer.

Start using the Mnemonic MCP today

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We've already built the connector for Mnemonic. Just plug in your AI agents and start using Vinkius.

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