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

Q: How do teams share Lucidworks Fusion (AI Search & Discovery) configurations in VS Code Copilot?

You can commit your configuration to your repository in a .vscode/mcp.json file. This lets your team share the MCP Server setup automatically.

Q: Can VS Code Copilot monitor indexing jobs in Lucidworks Fusion (AI Search & Discovery)?

Yes, Copilot can call lw.listjobs to check active indexing and training tasks. This helps your team verify that background processes are running smoothly.

Q: Does this integration support custom JSON payloads for Solr?

Yes, the server exposes lw.postcustomquery to let your team test custom vector parameters. Copilot can generate and run these payloads directly in the editor.

Share real-time Lucidworks Fusion search tools across your engineering team in VS Code Copilot.

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Connect Lucidworks Fusion (AI Search & Discovery) MCP to VS Code Copilot

Create your Vinkius account to connect Lucidworks Fusion (AI Search & Discovery) to VS Code Copilot 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 VS Code Copilot

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Team-wide search integration with this MCP Server

Verifying search behavior against live Fusion query profiles is handled by `lw.query_search` to keep your entire development team in sync using this MCP setup. Your developers can run test queries directly against production-like environments. When debugging complex sorting logic, your team can use `lw.query_sorted` to test results on the fly. This ensures everyone is testing against the same active sorting arrays.

Track ML training pipelines during code reviews

Monitoring active training runs is done using the `lw.list_jobs` tool, which lets Copilot inspect background processes right inside your pull request reviews. This visibility keeps your team informed about relevance model updates. To verify that user actions are being recorded properly, developers can test `lw.post_signal` directly. Running telemetry checks in your editor prevents bad tracking code from hitting production.

Validate document indexing pipelines instantly

You run `lw.index_documents` to push test payloads and verify document parser extraction logic instantly inside VS Code. Having this capability prevents broken index schemas during collaborative updates. If you need to verify how those documents are being processed, calling `lw.list_index_profiles` shows the active rules. This keeps your pipeline configurations visible to the entire team.

Setup guide

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

Prerequisites

VS Code 1.99 or later with GitHub Copilot extension
Active Vinkius subscription with a valid endpoint token

1

Open MCP configuration

Open the Command Palette (Cmd+Shift+P / Ctrl+Shift+P) and run "MCP: Add Server". Select HTTP (Streamable) as the server type. VS Code will create .vscode/mcp.json in your workspace.
2

Add the Lucidworks Fusion (AI Search & Discovery) MCP

Paste the JSON snippet shown on the right into your .vscode/mcp.json. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Switch to Agent mode

Open Copilot Chat (Cmd+Shift+I / Ctrl+Shift+I) and switch to Agent mode using the dropdown. MCP tools are only available in Agent mode — they do not appear in Edit or Ask modes.
4

Verify the connection

In the Copilot Chat input, type # to list available tools. You should see the Lucidworks Fusion (AI Search & Discovery) tools listed. Try asking: "List my recent Lucidworks Fusion (AI Search & Discovery) transactions" and Copilot will invoke them automatically.

.vscode/mcp.json

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

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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 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 VS Code Copilot

You can commit your configuration to your repository in a `.vscode/mcp.json` file. This lets your team share the MCP Server setup automatically.

Yes, Copilot can call `lw.list_jobs` to check active indexing and training tasks. This helps your team verify that background processes are running smoothly.

Copilot invokes the tool through the MCP Server to apply specific metadata filters. This lets you debug complex search restrictions directly from your chat sidebar.

Yes, the server exposes `lw.post_custom_query` to let your team test custom vector parameters. Copilot can generate and run these payloads directly in the editor.

All telemetry and search queries are handled through enterprise-grade, SOC 2 compliant connections. Your telemetry data is routed directly to your Fusion instance without passing through third-party servers.

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