How to Use the Baidu Qianfan MCP in VS Code Copilot

Q: Can VS Code Copilot check Baidu Qianfan training runs?

Yes, by calling the listtrainjobs tool. The agent fetches the current status metrics and displays them in your chat window.

Q: Why does Baidu Qianfan fail to return embeddings in VS Code Copilot?

The getembeddings tool might time out on massive text blocks. Try sending a smaller chunk of text to verify the connection is working.

Share Baidu Qianfan tools across your engineering team in VS Code Copilot via a single MCP Server configuration file.

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Connect Baidu Qianfan MCP to VS Code Copilot

Create your Vinkius account to connect Baidu Qianfan 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 Baidu Qianfan with VS Code Copilot

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Test Baidu Models in VS Code Copilot

The `chat_completions` tool connects your editor directly to Baidu's language models. Copilot sends your test queries to the API and drops the actual JSON response into your workspace. Your whole team tests against the same endpoints. Prototyping visual features works exactly the same way. The `text_to_image` tool executes text prompts and returns images inside the chat panel. This MCP integration means nobody has to open a browser window to verify a prompt.

Standardize Vector Generation

The `get_embeddings` tool pulls text vectors straight from the source. You get the exact array structures needed to write your database queries. Every developer on the project works with the identical vector format. Managing remote assets happens from the command palette. Running `list_datasets` shows the active training files. You stop guessing which dataset ID belongs in the configuration file.

Track Deployments with Your MCP Server

The `list_models` tool fetches the active service endpoints from your provider. Copilot reads this list and helps you update your routing logic to match what is actually deployed. Keeping tabs on fine-tuning is built right in. The `list_train_jobs` tool reports the exact status of your custom model runs. Your team knows immediately when a new model is ready for testing.

Setup guide

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

.vscode/mcp.json

{
  "mcpServers": {
    "baidu-qianfan-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Baidu Qianfan. 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 Baidu Qianfan MCP in VS Code Copilot

Add a .vscode/mcp.json file to your repository root. Paste the Vinkius URL inside. Commit the file so everyone gets the tools automatically.

Yes, by calling the list_train_jobs tool. The agent fetches the current status metrics and displays them in your chat window.

These features require version 1.96 or higher. Older builds do not support the agent mode required to execute external operations.

The get_embeddings tool might time out on massive text blocks. Try sending a smaller chunk of text to verify the connection is working.

Vinkius executes every tool call in an isolated, zero-trust sandbox. Your prompt text, embedding vectors, and dataset names pass through memory and disappear entirely once the connection closes.

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