Cohere (Embed & Rerank) MCP Server for Mastra AI 6 tools — connect in under 2 minutes
Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect Cohere (Embed & Rerank) through the Vinkius and Mastra agents discover all tools automatically — type-safe, streaming-ready, and deployable anywhere Node.js runs.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import { Agent } from "@mastra/core/agent";
import { createMCPClient } from "@mastra/mcp";
import { openai } from "@ai-sdk/openai";
async function main() {
// Your Vinkius token — get it at cloud.vinkius.com
const mcpClient = await createMCPClient({
servers: {
"cohere-embed-rerank": {
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
},
});
const tools = await mcpClient.getTools();
const agent = new Agent({
name: "Cohere (Embed & Rerank) Agent",
instructions:
"You help users interact with Cohere (Embed & Rerank) " +
"using 6 tools.",
model: openai("gpt-4o"),
tools,
});
const result = await agent.generate(
"What can I do with Cohere (Embed & Rerank)?"
);
console.log(result.text);
}
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.
Mastra's agent abstraction provides a clean separation between LLM logic and Cohere (Embed & Rerank) tool infrastructure. Connect 6 tools through the Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution — deployable to any Node.js host in one command.
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 Mastra AI 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 Mastra AI via MCP
Follow these steps to integrate the Cohere (Embed & Rerank) MCP Server with Mastra AI.
Install dependencies
Run npm install @mastra/core @mastra/mcp @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.ts and run with npx tsx agent.ts
Explore tools
Mastra discovers 6 tools from Cohere (Embed & Rerank) via MCP
Why Use Mastra AI with the Cohere (Embed & Rerank) MCP Server
Mastra AI provides unique advantages when paired with Cohere (Embed & Rerank) through the Model Context Protocol.
Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure — add Cohere (Embed & Rerank) without touching business code
Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation
TypeScript-native: full type inference for every Cohere (Embed & Rerank) tool response with IDE autocomplete and compile-time checks
One-command deployment to any Node.js host — Vercel, Railway, Fly.io, or your own infrastructure
Cohere (Embed & Rerank) + Mastra AI Use Cases
Practical scenarios where Mastra AI combined with the Cohere (Embed & Rerank) MCP Server delivers measurable value.
Automated workflows: build multi-step agents that query Cohere (Embed & Rerank), process results, and trigger downstream actions in a typed pipeline
SaaS integrations: embed Cohere (Embed & Rerank) as a first-class tool in your product's AI features with Mastra's clean agent API
Background jobs: schedule Mastra agents to query Cohere (Embed & Rerank) on a cron and store results in your database automatically
Multi-agent systems: create specialist agents that collaborate using Cohere (Embed & Rerank) tools alongside other MCP servers
Cohere (Embed & Rerank) MCP Tools for Mastra AI (6)
These 6 tools become available when you connect Cohere (Embed & Rerank) to Mastra AI 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 Mastra AI
Ready-to-use prompts you can give your Mastra AI 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 Mastra AI
Common issues when connecting Cohere (Embed & Rerank) to Mastra AI through the Vinkius, and how to resolve them.
createMCPClient not exported
npm install @mastra/mcpCohere (Embed & Rerank) + Mastra AI FAQ
Common questions about integrating Cohere (Embed & Rerank) MCP Server with Mastra AI.
How does Mastra AI connect to MCP servers?
MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.Can Mastra agents use tools from multiple servers?
Does Mastra support workflow orchestration?
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 Mastra AI
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.