How to Use the Mirror.xyz (Web3 Publishing Platform) MCP in Google ADK

Run deep semantic analysis on Mirror.xyz publications using Gemini's million-token context via the Google ADK.

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Connect Mirror.xyz (Web3 Publishing Platform) MCP to Google ADK

Create your Vinkius account to connect Mirror.xyz (Web3 Publishing Platform) 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 Mirror.xyz (Web3 Publishing Platform) with Google ADK

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Feed Arweave essays to Gemini long-context windows

The `get_entry` tool pulls raw markdown content from Arweave via its transaction digest. Because Gemini models handle massive token limits, your Google ADK agent can ingest dozens of full-length Web3 essays simultaneously. This setup bypasses traditional text-splitting or vector database indexing. You feed the raw, unedited markdown directly to the model, preserving the original formatting and footnotes for precise analysis.

Extract ENS publication histories with this MCP Server

The `get_entries` tool queries the Mirror GraphQL API using an ENS domain to return a structured list of post digests. Your Google ADK agent parses this historical list to build chronological author profiles. You can direct this output straight into BigQuery. Combining Web3 publishing metadata with your existing enterprise datasets allows you to track decentralized media trends over time.

Restrict tool access for enterprise security

The McpToolset class allows you to filter which operations are exposed to Gemini. If you only want your agent to read specific posts, you can restrict it to `get_entry` and block directory discovery. This granular control prevents the agent from executing unauthorized queries. It keeps your Google Cloud infrastructure compliant with internal data governance policies while interacting with public blockchain networks.

Setup guide

Set up Mirror.xyz (Web3 Publishing Platform) 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 Mirror.xyz (Web3 Publishing Platform) 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="Mirror.xyz (Web3 Publishing Platform)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Mirror.xyz (Web3 Publishing Platform) tools via MCP.",
    tools=mcp_tools,
)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Mirror.xyz. 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 Mirror.xyz (Web3 Publishing Platform) MCP in Google ADK

Use McpToolset with StreamableHttpServerParameters pointing to your Vinkius URL. Pass this toolset directly to your LlmAgent instance in Python.

Absolutely. You can combine this MCP toolset with your existing BigQuery tools, allowing Gemini to fetch decentralized content and write analysis directly to your cloud warehouse.

Yes, it works with any Gemini model supported by the ADK. The long-context window of Gemini 1.5 Pro is ideal for processing the large markdown files returned by the server.

The Google ADK integration supports both Stdio and HTTP transports. For hosted cloud deployments, HTTP transport via Vinkius is the recommended path.

The server only requests public ENS domains and Arweave digests to fetch open-source blockchain data. Vinkius executes these requests in an isolated, zero-trust sandbox, ensuring no proprietary enterprise data leaks to the public web.

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