How to Use the Cohere MCP in Vercel AI SDK

Q: How do I stream Cohere chat responses using the Vercel AI SDK?

Install @ai-sdk/mcp and call the Cohere chat tool within your Vercel streamText function. This pipes the live token stream from Command-R-Plus directly to your frontend components.

Q: How does the Vercel AI SDK handle Cohere token limit errors?

You can use the tokenize tool to check the size of your prompt array before calling the LLM. This lets your TypeScript code truncate or split the text to avoid API errors.

Q: What is the fastest way to list available models?

Call the listmodels tool. It returns every active endpoint, context window size, and tokenization parameter directly to your application logic.

Pipe real-time Cohere Command chat and reranked search results directly into your React UI using the Vercel AI SDK.

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Connect Cohere MCP to Vercel AI SDK

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

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Rerank Next.js search results via Vercel AI SDK and Cohere

The Cohere `rerank` tool lets your Vercel application reorder raw database results based on actual semantic relevance to the user's search query. By feeding these ranked results directly into your edge-rendered Next.js pages, you bypass heavy database operations and get instant, highly relevant results. You don't need to spin up a separate Python service to handle the heavy math. This MCP Server lets your Vercel AI SDK setup call `rerank-v3.5` directly from an Edge Function, keeping your bundle size tiny and your UI snappy.

Stream Command-R chat with live citations

The Cohere `chat` tool connects your React frontend to Command-R models for multi-turn conversations complete with source citations. Using the Vercel AI SDK, users see the Cohere text and references render block-by-block so they aren't staring at a blank loading screen. Setting up the Cohere MCP Server connection takes a few lines of TypeScript. Once connected, the Command-R model's structured citations feed straight into your Vercel AI SDK stream, letting you render clickable source cards on the fly.

Track token counts on the edge

The Cohere `tokenize` and `detokenize` tools let your Next.js edge middleware inspect the exact footprint of user prompts before sending them to Command-R-Plus. It's easy to control your Cohere API spend by checking token lengths directly in your Vercel serverless functions. Using these tokenizing tools with the Vercel AI SDK prevents runaway Cohere costs from giant system prompts. You can truncate inputs dynamically on the fly, ensuring your Vercel serverless executions never hit timeout limits.

Setup guide

Set up Cohere 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 Cohere 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 Cohere 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 Cohere. 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 Cohere MCP in Vercel AI SDK

Install `@ai-sdk/mcp` and call the Cohere `chat` tool within your Vercel `streamText` function. This pipes the live token stream from Command-R-Plus directly to your frontend components.

Yes, this Vercel-compatible MCP Server works with Edge Functions. You call the Cohere `rerank` tool inside your Next.js route handler to order search results before sending them to the client.

You can use the `tokenize` tool to check the size of your prompt array before calling the LLM. This lets your TypeScript code truncate or split the text to avoid API errors.

Call the `list_models` tool. It returns every active endpoint, context window size, and tokenization parameter directly to your application logic.

Your raw text, token IDs, and search documents pass through Vinkius's secure, isolated sandbox before reaching the Cohere API. No data is cached or stored locally on our servers during these operations.

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