Accept Language Parser MCP Server for OpenAI Agents SDKGive OpenAI Agents SDK instant access to 1 tools to Parse Accept Language
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Accept Language Parser through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.
Ask AI about this MCP Server for OpenAI Agents SDK
The Accept Language Parser MCP Server for OpenAI Agents SDK is a standout in the Productivity category — giving your AI agent 1 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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="Accept Language Parser Assistant",
instructions=(
"You help users interact with Accept Language Parser. "
"You have access to 1 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Accept Language Parser"
)
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 Accept Language Parser MCP Server
When a global routing agent reads Accept-Language: en-US,pt-BR;q=0.9,fr;q=0.8, it needs to correctly parse quality weights and determine the user's preferred language. This MCP does it deterministically.
The OpenAI Agents SDK auto-discovers all 1 tools from Accept Language Parser through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Accept Language Parser, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
The Superpowers
- RFC 7231 Compliant: Parses quality values (q-factors) exactly as specified by the HTTP standard.
- Priority Ordered: Returns languages sorted by quality weight, with the preferred language first.
The Accept Language Parser MCP Server exposes 1 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 1 Accept Language Parser tools available for OpenAI Agents SDK
When OpenAI Agents SDK connects to Accept Language Parser through Vinkius, your AI agent gets direct access to every tool listed below — spanning http-headers, localization, language-detection, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.
Parse accept language on Accept Language Parser
Pass the raw header value (e.g. "en-US,pt-BR;q=0.9,fr;q=0.8") and receive a priority-ordered list of languages with their quality weights. Never try to parse quality weights manually. Parses HTTP Accept-Language headers into an ordered list of user language preferences with quality weights. Essential for global routing and i18n agents
Connect Accept Language Parser to OpenAI Agents SDK via MCP
Follow these steps to wire Accept Language Parser into OpenAI Agents SDK. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.
Install the SDK
pip install openai-agents in your Python environmentReplace the token
[YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.comRun the script
python agent.pyExplore tools
Why Use OpenAI Agents SDK with the Accept Language Parser MCP Server
OpenAI Agents SDK provides unique advantages when paired with Accept Language Parser 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
Accept Language Parser + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Accept Language Parser MCP Server delivers measurable value.
Automated workflows: build agents that query Accept Language Parser, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries Accept Language Parser, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Accept Language Parser tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Accept Language Parser to resolve tickets, look up records, and update statuses without human intervention
Example Prompts for Accept Language Parser in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Accept Language Parser immediately.
"Parse this Accept-Language header: en-US,pt-BR;q=0.9,fr;q=0.8"
"What is the user's preferred language from: de,en-GB;q=0.7,ja;q=0.3"
"How many languages does the browser support based on this header: zh-CN,zh;q=0.9,en;q=0.8,ko;q=0.7,ar;q=0.6"
Troubleshooting Accept Language Parser MCP Server with OpenAI Agents SDK
Common issues when connecting Accept Language Parser to OpenAI Agents SDK through Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Accept Language Parser + OpenAI Agents SDK FAQ
Common questions about integrating Accept Language Parser 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?
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