Ragas MCP Server for Vercel AI SDK 7 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Ragas through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.
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Vinkius supports streamable HTTP and SSE.
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
async function main() {
const mcpClient = await createMCPClient({
transport: {
type: "http",
// Your Vinkius token. get it at cloud.vinkius.com
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
});
try {
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "Using Ragas, list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
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 Ragas MCP Server
Integrate Ragas with your AI agent to bring professional grade RAG (Retrieval-Augmented Generation) evaluation and tracking into your chat interface. By subscribing to this server, the AI can seamlessly manage datasets and measure LLM performance on demand.
The Vercel AI SDK gives every Ragas tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 7 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
What you can do
- Dataset Management — Upload, list, and organize evaluation datasets directly inside your environment.
- Run Evaluations — Automatically trigger Ragas evaluations on your RAG pipelines and fetch detailed scoring.
- Track Experiments — Monitor and compare iterative improvements by viewing tracked metrics across different agent versions.
- Project Organization — Associate evaluations with specific projects within your Ragas dashboard.
The Ragas MCP Server exposes 7 tools through the Vinkius. Connect it to Vercel AI SDK 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 Ragas to Vercel AI SDK via MCP
Follow these steps to integrate the Ragas MCP Server with Vercel AI SDK.
Install dependencies
Run npm install @ai-sdk/mcp ai @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the script
Save to agent.ts and run with npx tsx agent.ts
Explore tools
The SDK discovers 7 tools from Ragas and passes them to the LLM
Why Use Vercel AI SDK with the Ragas MCP Server
Vercel AI SDK provides unique advantages when paired with Ragas through the Model Context Protocol.
TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Ragas integration everywhere
Built-in streaming UI primitives let you display Ragas tool results progressively in React, Svelte, or Vue components
Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
Ragas + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Ragas MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Ragas in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Ragas tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Ragas capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Ragas through natural language queries
Ragas MCP Tools for Vercel AI SDK (7)
These 7 tools become available when you connect Ragas to Vercel AI SDK via MCP:
get_dataset
Retrieves details for a specific evaluation dataset
get_experiment
Retrieves detailed information for a specific experiment
get_results
Retrieves the results of a completed experiment
list_datasets
Lists available evaluation datasets
list_experiments
Lists experiments associated with a specific dataset
list_metrics
Lists all available evaluation metrics
run_evaluation
g., faithfulness, answer_relevancy). Triggers a new evaluation run for a dataset
Example Prompts for Ragas in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Ragas immediately.
"List all Ragas datasets available in my project."
"Fetch the metrics and results for the recent experiment 'Support Bot V3'."
"Create a new Ragas project named 'Financial_RAG_Testing'."
Troubleshooting Ragas MCP Server with Vercel AI SDK
Common issues when connecting Ragas to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpRagas + Vercel AI SDK FAQ
Common questions about integrating Ragas MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.Can I use MCP tools in Edge Functions?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.Connect Ragas 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 Ragas to Vercel AI SDK
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.