How to Use the Voyage AI (AI Embeddings API) MCP in VS Code Copilot

Q: How do I use Voyage AI (AI Embeddings API) with VS Code Copilot?

You commit the server configuration to .vscode/mcp.json in the project root. This makes it available automatically to every developer on your team, making the tools universally accessible.

Q: Can Voyage AI (AI Embeddings API) handle multimodal data in VS Code Copilot?

Yes. The createmultimodalembeddings tool lets you index complex assets—like diagrams or media files—alongside your code. This means the team's knowledge base isn't limited to text alone.

Q: How do I manage my data when using Voyage AI (AI Embeddings API) with VS Code Copilot?

The team can use listfiles and getfilecontent to inspect documentation. If a file is deprecated, the server provides deletefile, giving IT administrators full control over the knowledge base.

Team-wide embeddings and RAG context for every developer using VS Code Copilot.

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Connect Voyage AI (AI Embeddings API) MCP to VS Code Copilot

Create your Vinkius account to connect Voyage AI (AI Embeddings API) 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 Voyage AI (AI Embeddings API) with VS Code Copilot

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Generating Embeddings via Shared Config

The `create_embeddings` tool generates the core vector representations for your codebase. By configuring this in `.vscode/mcp.json`, every developer on the team automatically gains access to generate and use these embeddings. When Copilot Chat acts as an agent, it calls these tools directly, pulling fresh context from the defined knowledge base without needing manual setup.

Reranking Documents for Team Consistency

Teamwork requires consistent answers. Use `rerank` to standardize how documents are retrieved and prioritized against a query. This mechanism ensures that every developer, regardless of who asks the question, gets the same top-ranked context. This process improves code suggestion quality by filtering out noise and focusing on the most relevant sections of your shared knowledge base.

Batch Processing for Enterprise Repos

Instead of manual file uploads, commit a batch job setup using `upload_file` in `.vscode/mcp.json`. This allows the entire team to run large-scale jobs via `create_batch`, managing status with `list_batches`. This makes onboarding new documentation or massive codebases seamless for everyone on the engineering team.

Setup guide

Set up Voyage AI (AI Embeddings API) 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 Voyage AI (AI Embeddings API) 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 Voyage AI (AI Embeddings API) tools listed. Try asking: "List my recent Voyage AI (AI Embeddings API) transactions" and Copilot will invoke them automatically.

.vscode/mcp.json

{
  "mcpServers": {
    "voyage-ai-ai-embeddings-api-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

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Common questions about Voyage AI (AI Embeddings API) MCP in VS Code Copilot

You commit the server configuration to `.vscode/mcp.json` in the project root. This makes it available automatically to every developer on your team, making the tools universally accessible.

Yes. The `create_multimodal_embeddings` tool lets you index complex assets—like diagrams or media files—alongside your code. This means the team's knowledge base isn't limited to text alone.

The configuration is managed via a committed file, ensuring that sensitive project data remains within the version control system and never requires external, unsecured endpoints.

N/A. VS Code Copilot runs locally within your IDE environment, so you don't rely on external web URLs or network connectivity to access the tools.

The team can use `list_files` and `get_file_content` to inspect documentation. If a file is deprecated, the server provides `delete_file`, giving IT administrators full control over the knowledge base.

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