How to Use the Tome (AI Storytelling) MCP in Vercel AI SDK

Q: How do I search for existing projects using Tome (AI Storytelling) and Vercel AI SDK?

You call listworkspaces first. This gives you a list of all the containers where your Tome projects live. Your agent then uses that data to build the next steps in your UI.

Q: Can I view specific Tome metadata using Tome (AI Storytelling) and Vercel AI SDK?

Yep. Use gettome with a specific ID. This pulls all the detailed info you need—like pages, owners, and status—and streams it to your client side.

Q: Does Tome (AI Storytelling) support adding new content through Vercel AI SDK?

It does. The addpage tool lets you programmatically add a brand-new page to an existing Tome. Your agent sends the command, and you see the confirmation stream back to the user.

Q: What's the best way to list available projects in my app with Tome (AI Storytelling) and Vercel AI SDK?

Just use listtomes. This function returns a clean array of all accessible Tomes within your current workspace. It’s fast, and it works great when streaming results.

See your AI generate and manage Tome (AI Storytelling) content live using Vercel AI SDK.

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Connect Tome (AI Storytelling) MCP to Vercel AI SDK

Create your Vinkius account to connect Tome (AI Storytelling) 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 Tome (AI Storytelling) with Vercel AI SDK

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Streamline UI Updates with the MCP Server

The `list_workspaces` tool lets your agent get all available Tome project containers in real-time. When you stream results using Vercel AI SDK, users see the workspace list appear instantly, without any loading spinners.

Real-Time Content Retrieval with Vercel AI SDK

Need to show a user their existing presentations? Call `get_tome` to pull specific Tome data directly into your React component. Because it's streaming, the UI updates as the detailed Tome information arrives, giving a genuinely live feel.

Building Dynamic Workflows with MCP Server

You can build multi-step UIs that manage content flow. For example, an agent uses `list_tomes` to see what's available, then passes the ID to another step that calls `add_page`. This whole process streams right into the user's view.

Setup guide

Set up Tome (AI Storytelling) 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 Tome (AI Storytelling) 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 Tome (AI Storytelling) 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 Tome. 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 Tome (AI Storytelling) MCP in Vercel AI SDK

You call `list_workspaces` first. This gives you a list of all the containers where your Tome projects live. Your agent then uses that data to build the next steps in your UI.

Yep. Use `get_tome` with a specific ID. This pulls all the detailed info you need—like pages, owners, and status—and streams it to your client side.

It does. The `add_page` tool lets you programmatically add a brand-new page to an existing Tome. Your agent sends the command, and you see the confirmation stream back to the user.

Just use `list_tomes`. This function returns a clean array of all accessible Tomes within your current workspace. It’s fast, and it works great when streaming results.

This server handles Tome workspaces and individual tomes. These are the containers and the content records that your agent reads and writes.

Use it with your favorite AI tools

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