Cohere (Embed & Rerank) MCP Server for Vercel AI SDK 6 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Cohere (Embed & Rerank) through the 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 Cohere (Embed & Rerank), 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 Cohere (Embed & Rerank) MCP Server
Connect your Cohere account to any AI agent and take full control of your enterprise AI and RAG workflows through natural conversation.
The Vercel AI SDK gives every Cohere (Embed & Rerank) tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 6 tools through the 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
- Text Embeddings — Generate precise dense vector shapes for plain strings to power semantic search and knowledge retrieval
- Semantic Reranking — Structure contextual chunks by priority ordering documents against specific queries for improved RAG accuracy
- Conversational AI — Execute formatted conversational transformations using Cohere's generation limits and state-of-the-art LLMs
- Text Classification — Categorize inputs into predefined labels using few-shot training blocks and extract confidence scores
- Tokenization — Retrieve exact structural segmentation of NLP contexts to audit token counts and model dictionaries
- Model Registry — Enumerate available Cohere models and hashes to verify API availability based on your plan
The Cohere (Embed & Rerank) MCP Server exposes 6 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 Cohere (Embed & Rerank) to Vercel AI SDK via MCP
Follow these steps to integrate the Cohere (Embed & Rerank) 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 6 tools from Cohere (Embed & Rerank) and passes them to the LLM
Why Use Vercel AI SDK with the Cohere (Embed & Rerank) MCP Server
Vercel AI SDK provides unique advantages when paired with Cohere (Embed & Rerank) 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 Cohere (Embed & Rerank) integration everywhere
Built-in streaming UI primitives let you display Cohere (Embed & Rerank) 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
Cohere (Embed & Rerank) + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Cohere (Embed & Rerank) MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Cohere (Embed & Rerank) in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Cohere (Embed & Rerank) tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Cohere (Embed & Rerank) capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Cohere (Embed & Rerank) through natural language queries
Cohere (Embed & Rerank) MCP Tools for Vercel AI SDK (6)
These 6 tools become available when you connect Cohere (Embed & Rerank) to Vercel AI SDK via MCP:
chat_completion
Execute explicitly formatted conversational transformations
classify_texts
Enumerate explicitly mapped string classes evaluating static limits
embed_texts
Identify precise dense vector shapes mapping semantic limits
list_models
Inspect internal properties detailing API availability
rerank_documents
Discover explicit routing arrays structuring specific contextual chunks
tokenize_text
Retrieve the exact structural segmentation limiting NLP contexts
Example Prompts for Cohere (Embed & Rerank) in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Cohere (Embed & Rerank) immediately.
"Generate embeddings for these texts: ['Hello world', 'Artificial Intelligence']"
"Rerank these documents for query 'Best pizza in NY': ['Pizza hut review', 'Joe's Pizza is the local favorite']"
"How many tokens are in the text: 'The quick brown fox jumps over the lazy dog'?"
Troubleshooting Cohere (Embed & Rerank) MCP Server with Vercel AI SDK
Common issues when connecting Cohere (Embed & Rerank) to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpCohere (Embed & Rerank) + Vercel AI SDK FAQ
Common questions about integrating Cohere (Embed & Rerank) 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 Cohere (Embed & Rerank) 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 Cohere (Embed & Rerank) to Vercel AI SDK
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.