How to Use the Accept Language Parser MCP in AutoGen

Q: How do AutoGen agents use Accept Language Parser to decide on a language?

The master agent passes the raw header to parseacceptlanguage. It then shares the sorted list of locales with the translation agent to decide the final output language.

Q: How do I add this MCP Server to an AssistantAgent in AutoGen?

Install autogen-extmcp, fetch the tools list using mcpservertools, and pass that list directly to your AssistantAgent constructor.

Give your AutoGen agents the ability to negotiate and agree on the best user language using parsed headers.

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Create your Vinkius account to connect Accept Language Parser to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Accept Language Parser with AutoGen

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AutoGen multi-agent language negotiation

By calling `parse_accept_language`, your AutoGen routing agent gets an objective, weighted list of user preferences to resolve language disagreements. In a multi-agent setup, your routing agent and translation agent might disagree on the best language to use. The agents can then debate the best fallback options based on the quality weights. They reach a consensus on whether to serve French or fall back to English before generating the UI.

Automated schema conversion for AutoGen

The `parse_accept_language` tool schema is automatically mapped to AutoGen's format using the MCP extension adapter to prevent agent execution errors. AutoGen requires strict tool schemas to keep agent loops running smoothly. Your agents call the tool with raw headers and receive clean JSON outputs. No manual schema mapping or custom parsing code is needed in your agent definitions.

State-free HTTP transport for AutoGen MCP Server

The `parse_accept_language` tool responds instantly over HTTP, allowing you to run your AutoGen agents in stateless environments. It keeps your agent loops fast and lightweight. Because the server doesn't maintain state, your distributed AutoGen agents can call it concurrently without session conflicts. This makes it perfect for high-traffic multi-agent deployments.

Setup guide

Set up Accept Language Parser MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Accept Language Parser tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Accept Language Parser_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Accept Language Parser data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Accept Language Parser_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Accept Language Parser data")
    print(result.messages[-1].content)

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Common questions about Accept Language Parser MCP in AutoGen

The master agent passes the raw header to `parse_accept_language`. It then shares the sorted list of locales with the translation agent to decide the final output language.

Yes, the server supports streamable MCP HTTP transport. You can configure `mcp_server_tools` with the Vinkius URL to make the tool available to all agents in your conversation.

Letting agents guess language preferences leads to inconsistent UI translation. This tool provides a single source of truth for user locales, ensuring all agents in the chat align on the same language.

Install `autogen-ext[mcp]`, fetch the tools list using `mcp_server_tools`, and pass that list directly to your AssistantAgent constructor.

The tool only reads the value of the Accept-Language header. It has no access to IP addresses, cookies, or user histories, and Vinkius runs the code in an ephemeral sandbox that discards the header data immediately.

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