How to Use the Linkup (AI Search & RAG) MCP in Google ADK

Q: How do I initialize Linkup (AI Search & RAG) inside a Google ADK project?

Install the package and create an McpToolset pointing to your Vinkius MCP Server endpoint. Pass this toolset into the LlmAgent constructor to give Gemini instant access to web search.

Q: Can I limit which agents in Google ADK can access Linkup (AI Search & RAG)?

Yes, you can filter the exposed tools. Simply specify toolnames='searchweb' when creating your toolset, ensuring sensitive agents don't gain web-fetching capabilities.

Q: How does Linkup (AI Search & RAG) handle Javascript-heavy sites when called from Google ADK?

The fetchurl tool handles complex SPA loops automatically on the server side. Your Gemini agent gets clean, rendered markdown without having to write custom scraping logic.

Inject real-time web context directly into your Google ADK enterprise agents to feed Gemini's massive context window.

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Connect Linkup (AI Search & RAG) MCP to Google ADK

Create your Vinkius account to connect Linkup (AI Search & RAG) 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 Linkup (AI Search & RAG) with Google ADK

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Feed Gemini's massive context window via this MCP Server

Gemini models thrive when you feed them massive amounts of data. This MCP Server lets your Google ADK agent use `fetch_url` to grab entire web pages, bypassing heavy JS protections to return clean text. Instead of hitting token limits, you can pack multiple deep web pages into a single prompt. Your agent gets the exact technical documentation it needs to make complex decisions without losing track of the original system instructions.

Ground BigQuery analytical agents with live web facts

Enterprise agents often need to combine internal database records with external market realities. When your Google ADK agent queries BigQuery, it can simultaneously run `search_web` to find the latest pricing or news. This creates a powerful hybrid reasoning loop. Your agent compares your historical cloud data with real-time web facts, giving you accurate, up-to-date business intelligence without manual research.

Restrict tools for safe cloud execution

Security teams hate exposing unnecessary tools to autonomous agents. When defining your MCP Server toolset in Python, you can use the optional tool filter to only expose `search_web` to specific public-facing agents. This ensures your internal database agents can't access arbitrary external URLs. You maintain strict control over what your Google ADK system can touch, keeping your cloud perimeter secure.

Setup guide

Set up Linkup (AI Search & RAG) 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 Linkup (AI Search & RAG) 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="Linkup (AI Search & RAG)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Linkup (AI Search & RAG) 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 Linkup. 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 Linkup (AI Search & RAG) MCP in Google ADK

Install the package and create an `McpToolset` pointing to your Vinkius MCP Server endpoint. Pass this toolset into the `LlmAgent` constructor to give Gemini instant access to web search.

Yes, you can filter the exposed tools. Simply specify `tool_names=['search_web']` when creating your toolset, ensuring sensitive agents don't gain web-fetching capabilities.

The `fetch_url` tool handles complex SPA loops automatically on the server side. Your Gemini agent gets clean, rendered markdown without having to write custom scraping logic.

It does. While Stdio is great for local testing, HTTP transport is the preferred choice for production agents deployed on Google Cloud Run or Vertex AI.

Your target URLs and fetched HTML content are processed entirely within secure, ephemeral V8 isolates. No search history or page data is stored permanently. Vinkius handles the authorization securely, ensuring your API keys are never exposed to the public web.

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