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

Q: How do I index documents in Lucidworks Fusion (AI Search & Discovery) with CrewAI?

Create a dedicated agent for data ingestion. Give it the lw.indexdocuments tool to process and push your records into the target collection.

Q: How can I monitor background jobs in Lucidworks Fusion (AI Search & Discovery) via CrewAI?

Use the lw.listjobs tool. A monitor agent can periodically check this and alert your human team if a job enters an error state.

Deploy a specialized crew of agents for Lucidworks Fusion. Automate search maintenance and relevance tuning at scale.

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Connect Lucidworks Fusion (AI Search & Discovery) MCP to CrewAI

Create your Vinkius account to connect Lucidworks Fusion (AI Search & Discovery) to CrewAI 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 CrewAI

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Assign research agents to query your index using `lw.query_search` while moderator agents verify the results. This multi-agent approach ensures higher accuracy in your search outputs. By splitting tasks, you reduce the load on any single agent. The crew maintains a shared memory of the search state, allowing for complex, multi-step investigations.

Automated document lifecycle management

Let your crew manage document health using `lw.index_documents` and `lw.list_collections`. An indexing agent can monitor incoming data and trigger ingestion jobs when needed. This keeps your index clean and up-to-date. You define the rules, and the crew executes them across your entire data set without manual input.

Advanced search signal processing

Configure an agent to analyze user behavior and call `lw.post_signal` to tune your search relevance. This creates a closed-loop system where the search engine constantly refines itself. Your agents watch the logs via `lw.list_jobs` and adjust the signal input. It is a persistent, hands-off way to maintain search quality.

Setup guide

Set up Lucidworks Fusion (AI Search & Discovery) MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Lucidworks Fusion (AI Search & Discovery) tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Lucidworks Fusion (AI Search & Discovery) Analyst",
    goal="Access and analyze Lucidworks Fusion (AI Search & Discovery) data via MCP.",
    backstory="Expert analyst with direct Lucidworks Fusion (AI Search & Discovery) access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Lucidworks Fusion (AI Search & Discovery) transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Lucidworks Fusion (AI Search & Discovery) Analyst",
        goal="Access and analyze Lucidworks Fusion (AI Search & Discovery) data via MCP.",
        backstory="Expert analyst with direct Lucidworks Fusion (AI Search & Discovery) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Lucidworks Fusion (AI Search & Discovery) transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

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 Lucidworks Fusion. 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 Lucidworks Fusion (AI Search & Discovery) MCP in CrewAI

Yes. Pass the server URL to your agent's MCP configuration. Then simply define a task that utilizes `lw.query_search` to find your target data.

Create a dedicated agent for data ingestion. Give it the `lw.index_documents` tool to process and push your records into the target collection.

It does. You can grant specific tools to specific agents. For example, only your 'manager' agent needs `lw.list_query_profiles` to change search rules.

Use the `lw.list_jobs` tool. A monitor agent can periodically check this and alert your human team if a job enters an error state.

The server only processes the raw text and metadata you provide. We enforce strict auth, and the data never leaves your environment; it is handled strictly between your crew and the Fusion instance.

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