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Cohere (Embed & Rerank) MCP Server for Cursor 6 tools — connect in under 2 minutes

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Cursor is an AI-first code editor built on VS Code that integrates LLM-powered coding assistance directly into the development workflow. Its Agent mode enables autonomous multi-step coding tasks, and MCP support lets agents access external data sources and APIs during code generation.

Vinkius supports streamable HTTP and SSE.

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Classic Setup·json
{
  "mcpServers": {
    "cohere-embed-rerank": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}
Cohere (Embed & Rerank)
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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.

Cursor's Agent mode turns Cohere (Embed & Rerank) into an in-editor superpower. Ask Cursor to generate code using live data from Cohere (Embed & Rerank) and it fetches, processes, and writes — all in a single agentic loop. 6 tools appear alongside file editing and terminal access, creating a unified development environment grounded in real-time information.

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 Cursor 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 Cursor via MCP

Follow these steps to integrate the Cohere (Embed & Rerank) MCP Server with Cursor.

01

Open MCP Settings

Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"

02

Add the server config

Paste the JSON configuration above into the mcp.json file that opens

03

Save the file

Cursor will automatically detect the new MCP server

04

Start using Cohere (Embed & Rerank)

Open Agent mode in chat and ask: "Using Cohere (Embed & Rerank), help me..."6 tools available

Why Use Cursor with the Cohere (Embed & Rerank) MCP Server

Cursor AI Code Editor provides unique advantages when paired with Cohere (Embed & Rerank) through the Model Context Protocol.

01

Agent mode turns Cursor into an autonomous coding assistant that can read files, run commands, and call MCP tools without switching context

02

Cursor's Composer feature can generate entire files using real-time data fetched through MCP — no copy-pasting from external dashboards

03

MCP tools appear alongside built-in tools like file reading and terminal access, creating a unified agentic environment

04

VS Code extension compatibility means your existing workflow, keybindings, and extensions all work alongside MCP tools

Cohere (Embed & Rerank) + Cursor Use Cases

Practical scenarios where Cursor combined with the Cohere (Embed & Rerank) MCP Server delivers measurable value.

01

Code generation with live data: ask Cursor to generate a security report module using live DNS and subdomain data fetched through MCP

02

Automated documentation: have Cursor query your API's tool schemas and generate TypeScript interfaces or OpenAPI specs automatically

03

Infrastructure-as-code: Cursor can fetch domain configurations and generate corresponding Terraform or CloudFormation templates

04

Test scaffolding: ask Cursor to pull real API responses via MCP and generate unit test fixtures from actual data

Cohere (Embed & Rerank) MCP Tools for Cursor (6)

These 6 tools become available when you connect Cohere (Embed & Rerank) to Cursor via MCP:

01

chat_completion

Execute explicitly formatted conversational transformations

02

classify_texts

Enumerate explicitly mapped string classes evaluating static limits

03

embed_texts

Identify precise dense vector shapes mapping semantic limits

04

list_models

Inspect internal properties detailing API availability

05

rerank_documents

Discover explicit routing arrays structuring specific contextual chunks

06

tokenize_text

Retrieve the exact structural segmentation limiting NLP contexts

Example Prompts for Cohere (Embed & Rerank) in Cursor

Ready-to-use prompts you can give your Cursor agent to start working with Cohere (Embed & Rerank) immediately.

01

"Generate embeddings for these texts: ['Hello world', 'Artificial Intelligence']"

02

"Rerank these documents for query 'Best pizza in NY': ['Pizza hut review', 'Joe's Pizza is the local favorite']"

03

"How many tokens are in the text: 'The quick brown fox jumps over the lazy dog'?"

Troubleshooting Cohere (Embed & Rerank) MCP Server with Cursor

Common issues when connecting Cohere (Embed & Rerank) to Cursor through the Vinkius, and how to resolve them.

01

Tools not appearing in Cursor

Ensure you are in Agent mode (not Ask mode). MCP tools only work in Agent mode.
02

Server shows as disconnected

Check Settings → Features → MCP and verify the server status. Try clicking the refresh button.

Cohere (Embed & Rerank) + Cursor FAQ

Common questions about integrating Cohere (Embed & Rerank) MCP Server with Cursor.

01

What is Agent mode and why does it matter for MCP?

Agent mode is Cursor's autonomous execution mode where the AI can perform multi-step tasks: reading files, editing code, running terminal commands, and calling MCP tools. Without Agent mode, Cursor operates in a simpler ask-and-answer mode that doesn't support tool calling. Always ensure you're in Agent mode when working with MCP servers.
02

Where does Cursor store MCP configuration?

Cursor looks for MCP server configurations in a mcp.json file. You can configure servers at the project level (.cursor/mcp.json in your project root) or globally (~/.cursor/mcp.json). Project-level configs take precedence.
03

Can Cursor use MCP tools in inline edits?

No. MCP tools are only available in Agent mode through the chat panel. Inline completions and Tab suggestions do not trigger MCP tool calls. This is by design — tool calls require user visibility and approval.
04

How do I verify MCP tools are loaded?

Open Settings → Features → MCP and look for your server name. A green indicator means the server is connected. You can also check Agent mode's available tools by clicking the tools dropdown in the chat panel.

Connect Cohere (Embed & Rerank) to Cursor

Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.