R2R MCP Server for Mastra AI 6 tools — connect in under 2 minutes
Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect R2R through Vinkius and Mastra agents discover all tools automatically. type-safe, streaming-ready, and deployable anywhere Node.js runs.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import { Agent } from "@mastra/core/agent";
import { createMCPClient } from "@mastra/mcp";
import { openai } from "@ai-sdk/openai";
async function main() {
// Your Vinkius token. get it at cloud.vinkius.com
const mcpClient = await createMCPClient({
servers: {
"r2r": {
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
},
});
const tools = await mcpClient.getTools();
const agent = new Agent({
name: "R2R Agent",
instructions:
"You help users interact with R2R " +
"using 6 tools.",
model: openai("gpt-4o"),
tools,
});
const result = await agent.generate(
"What can I do with R2R?"
);
console.log(result.text);
}
main();
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About R2R MCP Server
Connect your R2R (Rag to Riches) deployment to an AI agent, bringing your RAG infrastructure inside your chat interface. By linking this server, the AI can query its own constructed knowledge base on demand.
Mastra's agent abstraction provides a clean separation between LLM logic and R2R tool infrastructure. Connect 6 tools through Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution. deployable to any Node.js host in one command.
What you can do
- Vector Search — Perform semantic similarity queries across your document database to retrieve contextually relevant chunks of information.
- Execute RAG Queries — Use the 'rag_query' endpoint to have the R2R server directly summarize information based on vector data.
- Knowledge Management — Call the API to list ingested documents, read metadata attributes, and filter logical collections.
- Instance Health Monitoring — Quickly ping the connection using health checks to verify your system is responsive.
The R2R MCP Server exposes 6 tools through the Vinkius. Connect it to Mastra AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect R2R to Mastra AI via MCP
Follow these steps to integrate the R2R MCP Server with Mastra AI.
Install dependencies
Run npm install @mastra/core @mastra/mcp @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.ts and run with npx tsx agent.ts
Explore tools
Mastra discovers 6 tools from R2R via MCP
Why Use Mastra AI with the R2R MCP Server
Mastra AI provides unique advantages when paired with R2R through the Model Context Protocol.
Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure. add R2R without touching business code
Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation
TypeScript-native: full type inference for every R2R tool response with IDE autocomplete and compile-time checks
One-command deployment to any Node.js host. Vercel, Railway, Fly.io, or your own infrastructure
R2R + Mastra AI Use Cases
Practical scenarios where Mastra AI combined with the R2R MCP Server delivers measurable value.
Automated workflows: build multi-step agents that query R2R, process results, and trigger downstream actions in a typed pipeline
SaaS integrations: embed R2R as a first-class tool in your product's AI features with Mastra's clean agent API
Background jobs: schedule Mastra agents to query R2R on a cron and store results in your database automatically
Multi-agent systems: create specialist agents that collaborate using R2R tools alongside other MCP servers
R2R MCP Tools for Mastra AI (6)
These 6 tools become available when you connect R2R to Mastra AI via MCP:
get_document
Retrieves details for a specific document
get_health
Checks the health status of the R2R server
list_collections
Lists all document collections
list_documents
Lists all ingested documents in the R2R system
rag_query
Executes a RAG (Retrieval-Augmented Generation) query
search
Performs a vector search across ingested documents
Example Prompts for R2R in Mastra AI
Ready-to-use prompts you can give your Mastra AI agent to start working with R2R immediately.
"Perform a vector search for 'Company Holiday Policy 2026'."
"Query the RAG engine to summarize known advanced RAG chunking strategies."
"Verify the operational health of the R2R server."
Troubleshooting R2R MCP Server with Mastra AI
Common issues when connecting R2R to Mastra AI through the Vinkius, and how to resolve them.
createMCPClient not exported
npm install @mastra/mcpR2R + Mastra AI FAQ
Common questions about integrating R2R MCP Server with Mastra AI.
How does Mastra AI connect to MCP servers?
MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.Can Mastra agents use tools from multiple servers?
Does Mastra support workflow orchestration?
Connect R2R with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect R2R to Mastra AI
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.