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

Q: Can I run a search query with Lucidworks Fusion (AI Search & Discovery) using Claude Code?

Yes. Simply invoke lw.querysearch from your terminal. It returns the search results directly to your console, perfect for quick debugging or script automation.

Q: Does Lucidworks Fusion (AI Search & Discovery) integrate with Claude Code for automation?

It does. You can chain lw.listcollections with other tools in your CI pipeline. This lets you automate your search infrastructure management entirely through the command line.

Q: How do I log signals to Lucidworks Fusion (AI Search & Discovery) via Claude Code?

Use the lw.postsignal tool in your script. It sends the telemetry data to the server, allowing your ML models to adjust based on your automated testing.

Q: What tools are available for indexing in the terminal?

You have full access to lw.indexdocuments. This allows you to push bulk updates to your search index as part of your deployment process.

Claude Code brings Lucidworks Fusion (AI Search & Discovery) to your terminal, enabling headless search automation for your pipelines.

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Setup Lucidworks Fusion (AI Search & Discovery) with Claude Code

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Headless search queries in the terminal

Use `lw.query_search` directly in your shell scripts to pull data from your index. It returns JSON output that you can pipe into other CLI tools. This is ideal for CI/CD tasks that need to verify search results. You get the raw data you need without any UI overhead.

Custom JSON logic with `lw.post_custom_query`

When you need more than a standard search, this tool lets you pass custom JSON to the server. It maps your Solr vectors natively. This gives you full control over how your queries are processed. It is the most flexible way to interact with your index from a CLI environment.

Monitor index jobs headlessly

Run `lw.list_jobs` as part of your cron tasks to check on background processes. It identifies active arrays spanning your gateway auth. This ensures your search engine is always up to date. If a job fails, the output tells you exactly why, letting you fix it immediately.

Setup guide

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

Prerequisites

Claude Code CLI installed (npm install -g @anthropic-ai/claude-code)
Active Vinkius subscription with a valid endpoint token

1

Run the add command

Open your terminal and run the command shown on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com. Use --scope user to make it available across all projects.
2

Verify the connection

Start a Claude Code session and type /mcp to list connected servers. You should see lucidworks-fusion-ai-search-discovery-mcp with a green status indicator.
3

Start using tools

Ask Claude Code something like "Check my latest Lucidworks Fusion (AI Search & Discovery) transactions." It will automatically discover and invoke the available Lucidworks Fusion (AI Search & Discovery) tools.

Terminal

claude mcp add --transport http lucidworks-fusion-ai-search-discovery-mcp https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Get your connection token →

Prerequisites

Claude Code CLI installed
Active Vinkius subscription with a valid endpoint token

1

Open the config file

Create or edit .mcp.json in your project root for project-level scope, or ~/.claude.json for user-level scope.
2

Add the Lucidworks Fusion (AI Search & Discovery) MCP

Paste the JSON snippet shown on the right into the mcpServers object. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Restart Claude Code

Start a new Claude Code session. Type /mcp to confirm the server is connected. The tools will be automatically available in your conversation.

.mcp.json

{
  "mcpServers": {
    "lucidworks-fusion-ai-search-discovery-mcp": {
      "type": "url",
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Get your connection token →

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Common questions about Lucidworks Fusion (AI Search & Discovery) MCP in Claude Code

Yes. Simply invoke `lw.query_search` from your terminal. It returns the search results directly to your console, perfect for quick debugging or script automation.

It does. You can chain `lw.list_collections` with other tools in your CI pipeline. This lets you automate your search infrastructure management entirely through the command line.

Use the `lw.post_signal` tool in your script. It sends the telemetry data to the server, allowing your ML models to adjust based on your automated testing.

The server uses a single endpoint token for authentication. Your data is protected by strict vault limits, and no unauthorized process can access your collection records.

You have full access to `lw.index_documents`. This allows you to push bulk updates to your search index as part of your deployment process.

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