How to Use the LlamaIndex (AI Data Framework & RAG) MCP in Mastra AI
Build resilient RAG workflows with LlamaIndex (AI Data Framework & RAG) inside Mastra AI.
Works with every AI agent you already use
…and any MCP-compatible client
Connect LlamaIndex (AI Data Framework & RAG) MCP to Mastra AI
Create your Vinkius account to connect LlamaIndex (AI Data Framework & RAG) to Mastra AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Automate multi-step retrieval
Link your workflows to `query_pipeline` so your agents can fetch knowledge automatically. If a retrieval step fails, Mastra handles the retry logic for you. Your agents don't just query; they manage the flow. You define the logic, and the tools handle the heavy lifting of pulling context from your indexes.
Monitor index health
Keep tabs on your infrastructure by calling `list_indexes` within your workflow tasks. This allows for conditional branching based on which indexes are currently active. If you need to verify a specific index exists before running a search, perform a check first. It prevents errors by ensuring your agent targets the right resource every time.
Manage pipeline configurations
Use `get_pipeline` to pull live settings into your agent's decision-making process. This ensures your workflow always operates with the latest configuration parameters. Your code stays clean because you aren't hardcoding pipeline IDs. You query the server, get the config, and proceed with the task.
Set up LlamaIndex (AI Data Framework & RAG) MCP in Mastra AI
Prerequisites
- Node.js 18+ and a TypeScript project
-
@mastra/mcp+@mastra/corepackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
npm install @mastra/mcp @mastra/coreplus your preferred model provider (e.g.@ai-sdk/openai). - 2
Configure the MCPClient
Create an
MCPClientwith your Vinkius endpoint as aURLobject. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. - 3
Discover and inject tools
Call
mcpClient.listTools()and spread the result into your agent'stoolsobject. All LlamaIndex (AI Data Framework & RAG) tools become native Mastra tools. - 4
Run with any model
Swap
openai("gpt-4o")for any AI SDK-compatible provider. Callagent.generate()and the agent routes tool calls through MCP automatically.
import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";
const mcpClient = new MCPClient({
id: "llamaindex-ai-data-framework-rag-mcp-client",
servers: {
"llamaindex-ai-data-framework-rag-mcp": {
url: new URL(
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
),
},
},
});
const agent = new Agent({
name: "LlamaIndex (AI Data Framework & RAG) Agent",
model: openai("gpt-4o"),
instructions: "You have access to LlamaIndex (AI Data Framework & RAG) tools.",
tools: {
...(await mcpClient.listTools()),
},
});
const result = await agent.generate(
"List recent LlamaIndex (AI Data Framework & RAG) transactions"
);
console.log(result.text); 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 Mastra AI
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