How to Use the Redis Vector MCP in VS Code Copilot

Q: How do we share the Redis Vector MCP Server configuration across our VS Code Copilot team?

Create a .vscode/mcp.json file in your repository root. Once committed, any developer on your team using VS Code 1.96+ with Copilot gets access to the vector tools.

Q: Does this MCP Server support both cosine and L2 distance metrics in VS Code Copilot?

Yes, you can specify the distance metric when running createvectorindex. Copilot passes these parameters to the server to configure your RediSearch index.

Equipping your engineering team to query and manage Redis Vector indexes directly from VS Code Copilot.

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Setup Redis Vector with VS Code Copilot

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Run team-wide KNN searches directly in VS Code Copilot.

The `search_vectors` tool lets your engineering team run K-nearest neighbor similarity searches directly from the VS Code Copilot chat window. By committing the configuration to your repository, every developer gets instant access to live vector queries in VS Code. This setup eliminates the need for team members to write one-off test scripts outside of VS Code Copilot. Copilot calls the MCP Server to run searches and displays the raw float matches right beside your code.

Provision RediSearch indexes inside your shared workspace.

The `create_vector_index` tool allows VS Code Copilot to set up new vector indexes with specific dimensions and distance metrics. Your team can define a standard 1536-dimension index for production data directly from a VS Code Copilot chat prompt. To check the active schemas, VS Code Copilot uses `list_indexes` and `get_index_info` to check the active structures. This ensures that every developer using VS Code Copilot is writing code against the correct database structure.

Modify vector records directly from your Copilot chat.

The `upsert_vector` tool writes float arrays and document keys directly to your Redis hashes using VS Code Copilot commands. When debugging a pipeline, your developers can update vector records without leaving the VS Code editor. If a test document needs to be removed, VS Code Copilot invokes `delete_vector` to clear the hash. This keeps your shared development database clean and accurate during VS Code Copilot sprint cycles.

Setup guide

Set up Redis Vector 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 Redis Vector 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 Redis Vector tools listed. Try asking: "List my recent Redis Vector transactions" and Copilot will invoke them automatically.

.vscode/mcp.json

{
  "mcpServers": {
    "redis-vector-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 Redis Vector. 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 Redis Vector MCP in VS Code Copilot

Create a `.vscode/mcp.json` file in your repository root. Once committed, any developer on your team using VS Code 1.96+ with Copilot gets access to the vector tools.

Yes, as long as your MCP Server configuration points to your staging Redis instance, Copilot can execute similarity searches directly from the editor chat.

Copilot calls the tool with your specified index name and dimensions. The server registers the new RediSearch index, making it immediately available for your team.

Yes, you can specify the distance metric when running `create_vector_index`. Copilot passes these parameters to the server to configure your RediSearch index.

Yes, your float arrays, index names, and document keys are transmitted securely to your Redis instance. The MCP Server acts as a local proxy, ensuring sensitive vector data does not leak to public LLM endpoints.

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