How to Use the Accept Language Parser MCP in LlamaIndex

Q: How does LlamaIndex handle Accept Language Parser metadata filtering?

Pass the output of parseacceptlanguage to your index query engine as a metadata filter. LlamaIndex uses the parsed language codes to restrict document retrieval to matching translations.

Q: How do I register this MCP Server in LlamaIndex?

Use llama-index-tools-mcp to connect to the server URL. Convert the client to a tool list using totoollistasync and pass it to your FunctionAgent.

Index parsed user language preferences directly into your LlamaIndex knowledge graphs for localized RAG.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Accept Language Parser MCP to LlamaIndex

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

GDPR Free for Subscribers

Setup Accept Language Parser with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity

LlamaIndex semantic search by locale

The `parse_accept_language` tool extracts user language preferences from incoming request headers so you don't search your entire vector database in English if the user prefers Spanish. It helps you target the exact content your users need. LlamaIndex then uses these parsed locales to apply metadata filters to your index. This ensures your RAG pipeline only queries document chunks matching the user's actual language.

Indexing header parsed data in LlamaIndex

You can store the output of the `parse_accept_language` tool directly into your LlamaIndex document store to create a persistent record of user language preferences. This helps build rich user profiles over time. Future query engines can reference these indexed profiles. Your agent looks up past language weights to customize search results without calling the MCP server on every interaction.

Clean tool integration for index agents

Expose the `parse_accept_language` tool to your agent by registering the server with `llama-index-tools-mcp` to expose the MCP server's parsing capability. The tool returns a structured format that LlamaIndex's FunctionAgent understands out of the box. This eliminates manual string parsing in your Python code. The agent calls the tool, gets the structured locale list, and updates its query context.

Setup guide

Set up Accept Language Parser MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Accept Language Parser MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Accept Language Parser tools.",
)
response = await agent.run("List recent Accept Language Parser data")

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by accept-language-parser. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Accept Language Parser now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Accept Language Parser MCP in LlamaIndex

Pass the output of `parse_accept_language` to your index query engine as a metadata filter. LlamaIndex uses the parsed language codes to restrict document retrieval to matching translations.

Yes, you can convert the parsed language weights into node metadata or document attributes. This lets you build a searchable history of user language preferences across sessions.

LLM detection requires a full text input and costs tokens. This parser handles standard HTTP headers directly, giving you exact quality weights instantly so your index retrieval stays fast and cheap.

Use `llama-index-tools-mcp` to connect to the server URL. Convert the client to a tool list using `to_tool_list_async` and pass it to your FunctionAgent.

It only processes the raw HTTP Accept-Language string. The Vinkius MCP host ensures these header strings are never logged or stored, protecting your users' browser configuration data.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript