How to Use the Loopio MCP in Vercel AI SDK

Q: How do I search the Loopio library using AI SDK?

You initialize the client and pass the searchlibrary tool to your streamText function. The server returns matched entries directly to your frontend. It works just like any other tool call in your stack.

Q: Can AI SDK handle my Loopio project list?

Yes, just map listprojects to a button or an effect in your UI. It fetches the workspace state instantly. You get the full list of active RFPs ready for your users to select.

Stream approved Loopio answers directly into your AI SDK interface. Stop manual copying and start drafting responses in real-time.

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Connect Loopio MCP to Vercel AI SDK

Create your Vinkius account to connect Loopio to Vercel AI SDK 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 Loopio with Vercel AI SDK

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Claude

Perplexity

Search and fetch content with AI SDK

Trigger `search_library` to pull verified answers into your React or Next.js components instantly. Your UI updates as the data streams in, skipping the wait for loading spinners. You avoid stale data by querying the library before drafting. This keeps your response pipeline clean and accurate for every RFP.

Manage projects with AI SDK tools

Use `list_projects` to populate your dashboard with active RFPs. Your app gains full visibility into current workloads without leaving the editor. Once you pick a project, call `list_questionnaires` to map out the remaining tasks. You get a live feed of exactly what needs attention.

Automate submissions via MCP Server

Execute `create_submission` to push finalized responses back to the platform. Your AI client handles the heavy lifting of project creation while you maintain control over the output. Pair this with `get_questionnaire_responses` to verify everything looks right before you hit send. It keeps the audit trail intact.

Setup guide

Set up Loopio MCP in Vercel AI SDK

Prerequisites

Node.js 18+ and a TypeScript project
ai + @modelcontextprotocol/sdk packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies

Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).
2

Create the Streamable HTTP transport

Use StreamableHTTPClientTransport with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and use tools

Call mcpClient.tools() to auto-discover all Loopio tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.
4

Works with any model provider

Swap openai("gpt-4o") for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.

index.ts

import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const transport = new StreamableHTTPClientTransport(
  new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);

const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools,
  prompt: "List recent Loopio transactions",
});

console.log(text);
await mcpClient.close();

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 Loopio. 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 Loopio MCP in Vercel AI SDK

You initialize the client and pass the `search_library` tool to your `streamText` function. The server returns matched entries directly to your frontend. It works just like any other tool call in your stack.

Yes, just map `list_projects` to a button or an effect in your UI. It fetches the workspace state instantly. You get the full list of active RFPs ready for your users to select.

Your app only accesses what the provided token allows. Every query for `get_questionnaire_responses` stays within your authenticated session. We never store your RFP data on the server side.

That depends on your logic. You can use the MCP Server to draft the content, then show it to a user in the UI before calling `create_submission`. It's safer to gate the final write operation.

The server returns an error code. You should handle this in your UI by checking the response status. It's best to implement a small delay if you notice high traffic.

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