How to Use the Mention MCP in Google ADK

Connect Mention to your Google ADK pipelines to pipe social media sentiment directly into BigQuery.

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Connect Mention MCP to Google ADK

Create your Vinkius account to connect Mention 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 Mention with Google ADK

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Enterprise Sentiment Analysis with Google ADK

Large-scale brand monitoring requires serious analytical horsepower. By pairing this MCP Server with the Google ADK, your Gemini-powered agents can pull raw social data using `list_mentions` and feed it directly into BigQuery. This lets you run complex SQL queries on live public sentiment. Because Gemini handles massive context windows, your agent can pull hundreds of posts at once via `search_mentions`. It analyzes the collective mood of your audience without running out of memory.

Automate Alert Tracking in Google Cloud

Keep your enterprise response teams ahead of public trends. The agent calls `list_alerts` to monitor active trackers and immediately identifies sudden shifts in volume. It uses `get_alert_statistics` to generate data points that you can push to Vertex AI dashboards. If a specific alert flags a critical issue, the agent invokes `get_alert` to extract the parameters. This lets your Google ADK pipeline route the alert to the correct engineering or support queue instantly.

Track High-Value Brand Interactions

Not every social post deserves equal attention from your marketing team. This MCP Server keeps your Google ADK workflows focused on high-value accounts instead of chasing noise by using `list_favorite_mentions` to isolate flagged posts. You save hours of manual sorting. To understand who is involved, the agent calls `get_account_info` to map the workspace context. This ensures that any automated escalation is assigned to the correct regional team.

Setup guide

Set up Mention 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 Mention 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="Mention_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Mention 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 Mention. 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.

Why Choose Vinkius

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Common questions about Mention MCP in Google ADK

You configure your credentials once in the Vinkius dashboard. The Google ADK then connects to the managed endpoint using a single secure token, giving your agent immediate access to tools like `list_alerts`.

Yes, Gemini's million-token context window is perfect for this. Your agent can call `list_mentions` to retrieve large batches of posts and analyze long-term sentiment trends in a single turn.

Yes, the SDK supports both transport types. For cloud-deployed enterprise agents, the HTTP transport is recommended to connect securely to the managed Vinkius MCP Server gateway.

You can use the tool name filter parameter in the SDK initialization. This lets you restrict the agent to read-only tools like `get_mention_details` while hiding configuration tools.

All retrieved social posts and alert configurations are processed in isolated, zero-trust runtimes. Vinkius handles the transport securely, ensuring your MCP data is never exposed to the public web.

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