How to Use the LlamaIndex (AI Data Framework & RAG) MCP in Windsurf

Q: How do I query my RAG data using LlamaIndex (AI Data Framework & RAG) in Windsurf?

You use the querypipeline tool. Once the server is active, just ask Cascade to run a query, and it handles the tool call for you.

Q: Can Windsurf list all my active LlamaIndex (AI Data Framework & RAG) projects?

Yes. The listprojects tool fetches your project list directly from LlamaCloud. It maps out your workspace in seconds.

Q: How do I verify which files are ingested?

Run listfiles for a specific pipeline. It returns the raw source file list so you know exactly what your agent is referencing.

Connect LlamaIndex (AI Data Framework & RAG) to Windsurf. Let Cascade manage your RAG pipelines and query your data directly in the IDE.

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Connect LlamaIndex (AI Data Framework & RAG) MCP to Windsurf

Create your Vinkius account to connect LlamaIndex (AI Data Framework & RAG) to Windsurf 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 LlamaIndex (AI Data Framework & RAG) with Windsurf

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Autonomous RAG Pipeline Management

Cascade doesn't just read your data; it manages the pipeline lifecycle for you. Use `list_projects` and `list_pipelines` to survey your entire environment without leaving your editor. Once you identify the right pipeline, `get_pipeline` pulls the configuration so you can verify settings immediately. It turns manual auditing into a background task.

Direct Data Querying in Windsurf

Execute searches against your indexed documents using `query_pipeline`. You get the retrieval results right in your chat window, ready for context-aware code generation. It removes the need for external dashboards. If the results look off, you check the source using `list_files` to verify exactly what data is being pulled into the context window.

Index Inventory Control

Keep your project organized by calling `list_indexes` to see what is currently active in LlamaCloud. This keeps your search scope tight and accurate. When you need to debug a retrieval issue, you have the full list of available indexes at your fingertips. It keeps your workspace clean and your data retrieval focused.

Setup guide

Set up LlamaIndex (AI Data Framework & RAG) MCP in Windsurf

Prerequisites

Windsurf IDE installed (macOS, Windows, or Linux)
Active Vinkius subscription with a valid endpoint token

1

Open MCP configuration

Click the Cascade assistant icon in the sidebar, then click the hammer icon (🔨) at the top of the panel. Select "Configure" to open ~/.codeium/windsurf/mcp_config.json.
2

Add the LlamaIndex (AI Data Framework & RAG) MCP

Paste the JSON snippet shown on the right into the mcpServers object. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Refresh MCPs

Go back to the hammer icon (🔨) in Cascade and click "Refresh". Windsurf will detect the new server. No full restart is needed — the connection is hot-reloaded.
4

Verify in Cascade

Start a new Cascade conversation and ask something like "Show my LlamaIndex (AI Data Framework & RAG) payment history." If connected, Cascade will call the LlamaIndex (AI Data Framework & RAG) tools directly. You will see a green dot next to the server name in the MCP panel.

mcp_config.json

{
  "mcpServers": {
    "llamaindex-ai-data-framework-rag-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 LlamaIndex. 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 LlamaIndex (AI Data Framework & RAG) MCP in Windsurf

You use the `query_pipeline` tool. Once the server is active, just ask Cascade to run a query, and it handles the tool call for you.

Yes. The `list_projects` tool fetches your project list directly from LlamaCloud. It maps out your workspace in seconds.

It does. Once you add the server to your config, Cascade identifies the available tools automatically. You don't have to manually map anything.

Run `list_files` for a specific pipeline. It returns the raw source file list so you know exactly what your agent is referencing.

The server uses your own API key to connect to your private LlamaCloud instance. Your data never passes through Vinkius; it stays between your machine and your index.

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