How do I get a Cohere API Key?

Log in to the [**Cohere Dashboard**](https://dashboard.cohere.com/api-keys), 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.

What models are available?

Use the `list_models` tool 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).

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.

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 tool takes a query, list of documents and returns them ranked by relevance score. Cohere's rerank models are industry-leading for search applications.

Cohere MCP Server for OpenAI Agents SDK 6 tools — connect in under 2 minutes

Name: Cohere
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 6 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Cohere through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="Cohere Assistant",
            instructions=(
                "You help users interact with Cohere. "
                "You have access to 6 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Cohere"
        )
        print(result.final_output)

asyncio.run(main())

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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 MCP Server

Connect your Cohere account to any AI agent and leverage enterprise-grade AI models through natural conversation.

The OpenAI Agents SDK auto-discovers all 6 tools from Cohere through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Cohere, another analyzes results, and a third generates reports, all orchestrated through Vinkius.

What you can do

Model Discovery — List all available Cohere models with their names, capabilities and context lengths
Chat API — Send conversations to Command models (command-r-plus, command-r, command-r7b) and receive responses with citations and tool call support
Embeddings — Generate vector embeddings for semantic search with multiple embedding types (float, int8, uint8, binary)
Reranking — Rerank documents by relevance to a search query using Cohere's industry-leading reranking models
Tokenization — Tokenize and detokenize text for estimating token counts and debugging

The Cohere MCP Server exposes 6 tools through the Vinkius. Connect it to OpenAI Agents 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 to OpenAI Agents SDK via MCP

Follow these steps to integrate the Cohere MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 6 tools from Cohere

Why Use OpenAI Agents SDK with the Cohere MCP Server

OpenAI Agents SDK provides unique advantages when paired with Cohere through the Model Context Protocol.

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Cohere + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Cohere MCP Server delivers measurable value.

Automated workflows: build agents that query Cohere, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents. one queries Cohere, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Cohere tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Cohere to resolve tickets, look up records, and update statuses without human intervention

Cohere MCP Tools for OpenAI Agents SDK (6)

These 6 tools become available when you connect Cohere to OpenAI Agents SDK via MCP:

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 "tool") and "content" (text or array of content blocks). Optionally set max_tokens, temperature (0-1), p (nucleus sampling 0-1) and tools array for function calling. Returns the model's response with text, citations and tool calls. Send a chat message to a Cohere model

detokenize

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

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

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

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

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

Example Prompts for Cohere in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Cohere immediately.

"Send a message to Command R+ asking 'What is the capital of Brazil?'"

"Rerank these documents for the query 'machine learning models': ['Neural networks are inspired by biological neurons.', 'Python is a popular programming language.', 'Transformers use attention mechanisms for sequence processing.']"

"Generate embeddings for these texts: ['The weather is nice today.', 'I love programming in Python.'] using embed-v4."

Troubleshooting Cohere MCP Server with OpenAI Agents SDK

Common issues when connecting Cohere to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Cohere + OpenAI Agents SDK FAQ

Common questions about integrating Cohere MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.