How to Use the Marqo AI (Vector Search & Embeddings) MCP in VS Code Copilot

Q: How do I share Marqo AI (Vector Search & Embeddings) tools with my team in VS Code?

Add the server configuration to your project's .vscode/mcp.json file. Once committed to Git, your team members get the same tools automatically in their editors.

Q: Does Marqo AI (Vector Search & Embeddings) allow for index monitoring in VS Code?

Absolutely, just use getindexstats. It provides the team with real-time updates on document counts and index status.

Q: What is the primary way to update index documents for the whole team?

Use the adddocuments tool to push changes. It updates the index centrally so that all team members get the latest search results immediately.

Deploy Marqo AI (Vector Search & Embeddings) across your team in VS Code for shared semantic discovery.

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Connect Marqo AI (Vector Search & Embeddings) MCP to VS Code Copilot

Create your Vinkius account to connect Marqo AI (Vector Search & Embeddings) 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 Marqo AI (Vector Search & Embeddings) with VS Code Copilot

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Standardize search across the team

Commit your MCP configuration to `.vscode/mcp.json` so every team member has access to the same `tensor_search` capabilities. It removes the friction of manual setup and ensures everyone queries the same vector indices. Your team can rely on consistent semantic results during development. Because the configuration is version-controlled, you maintain a unified approach to data discovery across the entire organization.

Audit indices as a group

Use `list_indexes` to see the state of all shared collections. It allows your engineers to verify that they are targeting the correct index for their current feature work. Get visibility into index health with `get_index_stats`. When everyone on the team uses the same tools, debugging search relevance issues becomes a collaborative task rather than a siloed struggle.

Programmatic index management

Use `add_documents` and `delete_documents` to manage your shared dataset within VS Code. It is useful for updating product catalogs or documentation sets that your team needs to search against. These tools integrate into your standard Git-based workflow. By keeping your search logic and documentation in sync, you maintain high standards for your application's search performance.

Setup guide

Set up Marqo AI (Vector Search & Embeddings) 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 Marqo AI (Vector Search & Embeddings) 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 Marqo AI (Vector Search & Embeddings) tools listed. Try asking: "List my recent Marqo AI (Vector Search & Embeddings) transactions" and Copilot will invoke them automatically.

.vscode/mcp.json

{
  "mcpServers": {
    "marqo-ai-vector-search-embeddings-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 Marqo AI. 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 Marqo AI (Vector Search & Embeddings) MCP in VS Code Copilot

Add the server configuration to your project's `.vscode/mcp.json` file. Once committed to Git, your team members get the same tools automatically in their editors.

Yes, by connecting to a central Marqo instance, everyone can run `tensor_search` on the same indices. This ensures consistent search results across the entire engineering team.

Absolutely, just use `get_index_stats`. It provides the team with real-time updates on document counts and index status.

Data is processed only within your authorized Marqo instance. Vinkius manages the secure connection, ensuring that your team's search traffic remains isolated and protected.

Use the `add_documents` tool to push changes. It updates the index centrally so that all team members get the latest search results immediately.

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