DeepL MCP Server for OpenAI Agents SDK 9 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect DeepL through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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="DeepL Assistant",
instructions=(
"You help users interact with DeepL. "
"You have access to 9 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from DeepL"
)
print(result.final_output)
asyncio.run(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 DeepL MCP Server
Empower your AI agent to orchestrate your entire multilingual workflow with DeepL, the world's most accurate AI translator. By connecting DeepL to your agent, you transform complex translation tasks into a natural conversation. Your agent can instantly translate text between dozens of languages, audit available language pairs, and monitor API usage without you ever touching a technical dashboard. Whether you are localized content or communicating with international teams, your agent acts as a real-time linguistic bridge, ensuring your communication is always precise and professional.
The OpenAI Agents SDK auto-discovers all 9 tools from DeepL through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries DeepL, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.
What you can do
- Text Auditing — Translate text into target languages and retrieve detected source language metadata instantly.
- Linguistic Oversight — List all supported source and target languages to maintain a clear view of translation options.
- Usage Intelligence — Monitor your character count and API limits to maintain strict control over your translation budget.
- Glossary Management — List and query configured translation glossaries to ensure consistent brand terminology.
- Contextual Tone Control — Translate text enforcing strict formal, informal, or standard business tones instantly.
- Markup Preservation — Translate HTML elements while safely preserving tag boundaries and web structure.
The DeepL MCP Server exposes 9 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 DeepL to OpenAI Agents SDK via MCP
Follow these steps to integrate the DeepL 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 9 tools from DeepL
Why Use OpenAI Agents SDK with the DeepL MCP Server
OpenAI Agents SDK provides unique advantages when paired with DeepL 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
DeepL + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the DeepL MCP Server delivers measurable value.
Automated workflows: build agents that query DeepL, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents — one queries DeepL, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through DeepL tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query DeepL to resolve tickets, look up records, and update statuses without human intervention
DeepL MCP Tools for OpenAI Agents SDK (9)
These 9 tools become available when you connect DeepL to OpenAI Agents SDK via MCP:
get_account_glossaries
List configured translation glossaries
get_api_usage
Get current API usage and character limit constraints
get_glossary_dictionary
Get term mapping entries for a specific glossary ID
get_source_languages
List all supported source languages for translation
get_target_languages
g., EN-US, PT-BR) that DeepL can translate TO. List all supported target languages for translation
translate_html_markup
Translate HTML elements while preserving tag structure
translate_text_formal
g., "Sie" in German, "vous" in French) suitable for business communications. Translate text using a formal/business tone
translate_text_informal
g., "du" in German, "tu" in French) suitable for casual platforms. Translate text using an informal/casual tone
translate_text_standard
Translate text into a target language using standard tone
Example Prompts for DeepL in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with DeepL immediately.
"Translate 'Hello world' into Portuguese using DeepL."
"Show me all supported target languages in DeepL."
"What is my current DeepL usage?"
Troubleshooting DeepL MCP Server with OpenAI Agents SDK
Common issues when connecting DeepL to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
DeepL + OpenAI Agents SDK FAQ
Common questions about integrating DeepL MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect DeepL 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 DeepL to OpenAI Agents SDK
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.