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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use Cohere with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Access Cohere AI models via API. chat with Command models, generate embeddings, rerank documents and tokenize text from any AI agent.

Included with plan

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Complete set · 6 capabilities

The complete Cohere capability set.

These are the exact actions your AI can choose when you ask it to work with Cohere.

Capability set01 / 02

01-03

3 capabilities in this set.

Part of 6 available through Cohere.

  1. 01

    List models

    Each model returns its name (e.g. "command-r-plus", "command-r", "embed-v4", "rerank-v3.5"), endpoint compatibility, context length and tokenization info. Use this to discover which models are available and their capabilities. List all available Cohere models

  2. 02

    Tokenize

    Requires the text to tokenize and optionally the model. Returns the list of token IDs and token strings. Useful for estimating token counts before sending to chat or embed endpoints. Tokenize text using Cohere

  3. 03

    Chat

    Requires the model ID (e.g. "command-r-plus", "command-r", "command-r7b") and messages array in JSON format. Each message must have a "role" ("user", "assistant", "system" or "capability") and "content" (text or array of content blocks). Optionally set max_tokens, temperature (0-1), p (nucleus sampling 0-1) and capabilities array for function calling. Returns the model's response with text, citations and capability calls. Send a chat message to a Cohere model

Capability set02 / 02

04-06

3 capabilities in this set.

Part of 6 available through Cohere.

  1. 04

    Detokenize

    Requires the token IDs array. Returns the reconstructed text. Useful for debugging and verifying tokenization. Detokenize token IDs back to text using Cohere

  2. 05

    Rerank

    Requires the model ID (e.g. "rerank-v3.5", "rerank-english-v3.0"), query text and documents array. Optionally set top_n to return only the top N results. Returns ranked documents with relevance scores. Rerank documents by relevance to a query

  3. 06

    Embed

    Requires the model ID (e.g. "embed-v4", "embed-v3"), texts array and input_type ("search_document", "search_query", "classification", "clustering"). Returns embedding vectors for each input text. Useful for semantic search, similarity comparison and vector database storage. Generate embeddings using Cohere

Observed, not estimated

885ms average. Fast in production.

Cohere is checked daily against the live service.

Daily averagePeak 1060ms
Aug 20Today
Fastest day
702ms
Slowest day
1060ms
14-day trend
Slowing+31%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 6 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Cohere, so you can see the experience inside your AI.

It does not authenticate your account with Cohere. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Cohere Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_R4ERIik35jE1vo5hRbvNHBrwGzLbWOtl3sZQNmPU/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Cohere capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "cohere-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_R4ERIik35jE1vo5hRbvNHBrwGzLbWOtl3sZQNmPU/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

FAQ

Questions Cohere owners ask.

  • 01

    How do I get a Cohere API Key?

    Log in to the Cohere Dashboard, go to API Keys and click Create API Key. Copy the key immediately. it starts with a random string and won't be shown again. Free tier includes trial access with rate limits.

  • 02

    What models are available?

    Use the list_models capability to see all available Cohere models. Key models include command-r-plus (most capable, 128K context), command-r (efficient, 128K context), command-r7b (lightweight, 128K context), embed-v4 (embeddings) and rerank-v3.5 (reranking).

  • 03

    Can I send multi-turn conversations?

    Yes! Pass a messages array with alternating 'user', 'assistant' and 'system' roles. Each message has a 'role' and 'content' field. Command models support function calling and will return tool_calls when appropriate.

  • 04

    What is reranking and when should I use it?

    Reranking reorders a set of documents by their relevance to a query. Use it after an initial search to improve result quality. The rerank capability takes a query, list of documents and returns them ranked by relevance score. Cohere's rerank models are industry-leading for search applications.

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