How to Use the LunarCrush (Social Intelligence for Crypto Assets) MCP in Google ADK

Q: What is the setup process for configuring the LunarCrush (Social Intelligence for Crypto Assets) MCP Server inside a Google ADK agent?

Use McpToolset with StreamableHttpServerParameters pointing to your Vinkius URL for LunarCrush. Pass this toolset into the tools parameter of your Google ADK LlmAgent to make the LunarCrush MCP endpoints available.

Feed real-time crypto sentiment directly into Gemini long-context models using the Google ADK.

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Connect LunarCrush (Social Intelligence for Crypto Assets) MCP to Google ADK

Create your Vinkius account to connect LunarCrush (Social Intelligence for Crypto Assets) 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 LunarCrush (Social Intelligence for Crypto Assets) with Google ADK

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Pipe social metrics into BigQuery with Google ADK

Build data pipelines that combine Google Cloud storage with live LunarCrush crypto sentiment. By wrapping this LunarCrush MCP Server in `McpToolset`, your enterprise Gemini agents can pull real-time data using `get_social_metrics` and write it directly to BigQuery tables. This setup lets you run long-term correlation studies in Google ADK between LunarCrush social hype and actual trade execution. You can analyze months of LunarCrush market patterns without manual script maintenance.

Process massive asset lists in Gemini long context

Gemini's million-token window thrives on massive datasets like LunarCrush's entire token directory. Your Google ADK agent can call `list_assets` to pull hundreds of tracked tokens, then digest the entire list in a single reasoning loop. This eliminates the need to truncate LunarCrush data or run multiple chunked API requests in Google ADK. The Gemini model cross-references every coin against its current LunarCrush market performance in one go.

Track market sentiment shifts inside Vertex AI

Deploy autonomous agents on Google Cloud that monitor LunarCrush market health metrics. Using `get_market_metrics` alongside `get_altrank` in your Google ADK pipelines can flag unusual volume spikes. You can restrict which LunarCrush tools are exposed by passing a `tool_names` filter to your Google ADK toolset. This ensures your enterprise agents only access the specific LunarCrush endpoints they need.

Setup guide

Set up LunarCrush (Social Intelligence for Crypto Assets) 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 LunarCrush (Social Intelligence for Crypto Assets) 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="LunarCrush (Social Intelligence for Crypto Assets)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to LunarCrush (Social Intelligence for Crypto Assets) tools via MCP.",
    tools=mcp_tools,
)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by LunarCrush. 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 LunarCrush (Social Intelligence for Crypto Assets) MCP in Google ADK

Use `McpToolset` with `StreamableHttpServerParameters` pointing to your Vinkius URL for LunarCrush. Pass this toolset into the `tools` parameter of your Google ADK `LlmAgent` to make the LunarCrush MCP endpoints available.

Yes, your Gemini agent can query historical BigQuery tables and then call LunarCrush's `get_galaxy_score` to compare past trends with current social activity. This lets you build detailed Google ADK trading dashboards using LunarCrush data.

Vinkius manages the LunarCrush API keys securely, so your Google ADK code only needs a single MCP token. The ADK handles the underlying HTTP requests to the LunarCrush server directly.

You can use both Stdio and HTTP transports to connect the LunarCrush toolset to your Google ADK agent. HTTP is recommended for cloud-deployed Google Cloud Run services to ensure reliable scaling of your LunarCrush data pipeline.

Every LunarCrush tool execution occurs within isolated V8 containers on Vinkius, which means your queried crypto symbols and LunarCrush sentiment scores are never exposed. No data is stored permanently on the server side, meeting strict Google ADK enterprise compliance standards.

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