How to Use the Lucidworks Fusion (AI Search & Discovery) MCP in Google ADK

Q: How does Google ADK interact with Lucidworks Fusion (AI Search & Discovery) search profiles?

The agent calls lw.listqueryprofiles to discover active pipelines. It then uses lw.querysearch to execute queries against the selected profile, returning structured search results.

Q: Can I run sorted search queries using Google ADK?

Yes. The lw.querysorted tool allows your agent to specify sorting parameters like date or relevance scores to organize the search output before presenting it.

Q: How do I index real-time documents in Lucidworks Fusion (AI Search & Discovery) using Google ADK?

Your agent executes lw.indexdocuments to ingest new records directly. This ensures that new content is searchable immediately by your Gemini models.

Connect Lucidworks Fusion (AI Search & Discovery) to your Google ADK pipelines for long-context semantic search.

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Connect Lucidworks Fusion (AI Search & Discovery) MCP to Google ADK

Create your Vinkius account to connect Lucidworks Fusion (AI Search & Discovery) 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 Lucidworks Fusion (AI Search & Discovery) with Google ADK

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Query enterprise collections via Google ADK

`lw.query_search` allows Gemini models to run vector queries directly across your index. The agent uses its massive context window to digest search results and formulate highly accurate answers based on your raw data. You initialize this by passing the McpToolset to your LlmAgent. The agent discovers tools like `lw.list_collections` automatically, enabling it to choose the right data source for each user prompt.

Push search signals to train ML models

`lw.post_signal` captures user interactions to refine your search relevancy models over time. This tool sends click, purchase, or custom event data back to your cluster directly from the agent interface. The agent monitors these active training cycles via `lw.list_jobs`. This MCP connection lets you verify if machine learning models are updating without leaving your Google Cloud console.

Execute custom Solr logic with the MCP Server

`lw.post_custom_query` bypasses standard search pipelines to run raw JSON payloads against your Solr instances. This gives your agent the ability to apply custom boosting rules dynamically during a session. For structured query paths, the agent relies on `lw.list_query_profiles` to find pre-configured search rules. It then executes filtered queries using `lw.query_filtered` to restrict results to specific user accounts or regions.

Setup guide

Set up Lucidworks Fusion (AI Search & Discovery) 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 Lucidworks Fusion (AI Search & Discovery) 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="Lucidworks Fusion (AI Search & Discovery)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Lucidworks Fusion (AI Search & Discovery) tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Lucidworks Fusion (AI Search & Discovery) MCP in Google ADK

The agent calls `lw.list_query_profiles` to discover active pipelines. It then uses `lw.query_search` to execute queries against the selected profile, returning structured search results.

Yes. The `lw.query_sorted` tool allows your agent to specify sorting parameters like date or relevance scores to organize the search output before presenting it.

Your agent executes `lw.index_documents` to ingest new records directly. This ensures that new content is searchable immediately by your Gemini models.

The server supports both Stdio and HTTP transports. You configure it using StreamableHttpServerParameters to connect your agent to the hosted endpoint.

This MCP Server handles your Solr index schemas and credentials securely in V8 isolates. Only explicit query payloads from `lw.query_search` are transmitted, keeping your underlying collection structures completely hidden.

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