Language Detector Engine MCP Server for LlamaIndexGive LlamaIndex instant access to 1 tools to Detect Language
GDPR Free for SubscribersLlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Language Detector Engine as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this MCP Server for LlamaIndex
The Language Detector Engine MCP Server for LlamaIndex is a standout in the Customer Support 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
Geminiimport asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Language Detector Engine. "
"You have 1 tools available."
),
)
response = await agent.run(
"What tools are available in Language Detector Engine?"
)
print(response)
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 Language Detector Engine MCP Server
Your customer support agent receives a ticket: 'O produto não chegou'. The AI routes it to the Spanish queue. The agent wastes time, the customer gets angry, SLA drops. Why? Because the AI 'guessed' the language probabilistically instead of calculating it.
LlamaIndex agents combine Language Detector Engine tool responses with indexed documents for comprehensive, grounded answers. Connect 1 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
This MCP uses franc (200K+ weekly downloads, inspired by Google's CLD2) to perform deterministic N-gram language detection. It returns exact ISO 639-3 codes for over 400 languages, and properly returns 'undefined' if a text is too ambiguous rather than hallucinating.
The Superpowers
- 400+ Languages: From English (eng) and Portuguese (por) to Esperanto (epo) and Zulu (zul).
- Exact N-gram Math: Analyzes text strictly by character frequencies, not LLM probability.
- Whitelist/Blacklist: Know the text must be either Spanish or Portuguese? Pass
only: ['spa', 'por']to force a strict evaluation. - Confidence Scores: Use the
allflag to get an array of all matches with their exact probability scores.
The Language Detector Engine MCP Server exposes 1 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 1 Language Detector Engine tools available for LlamaIndex
When LlamaIndex connects to Language Detector Engine through Vinkius, your AI agent gets direct access to every tool listed below — spanning n-gram-analysis, language-detection, deterministic-logic, 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.
Detect language on Language Detector Engine
Provide as much text as possible for higher accuracy. Detect the language of any text using n-gram analysis. Supports 400+ languages. Returns ISO 639-3 codes (e.g., "por", "eng", "spa")
Connect Language Detector Engine to LlamaIndex via MCP
Follow these steps to wire Language Detector Engine into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Language Detector Engine MCP Server
LlamaIndex provides unique advantages when paired with Language Detector Engine through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Language Detector Engine tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Language Detector Engine tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Language Detector Engine, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Language Detector Engine tools were called, what data was returned, and how it influenced the final answer
Language Detector Engine + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Language Detector Engine MCP Server delivers measurable value.
Hybrid search: combine Language Detector Engine real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Language Detector Engine to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Language Detector Engine for fresh data
Analytical workflows: chain Language Detector Engine queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Language Detector Engine in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Language Detector Engine immediately.
"Detect the language of this support ticket: 'Não consigo acessar minha conta desde ontem'."
"We only support English and Spanish. Detect the language of 'Hola como estas' using the whitelist."
"Get the top 3 language probabilities for this ambiguous name: 'Alejandro'."
Troubleshooting Language Detector Engine MCP Server with LlamaIndex
Common issues when connecting Language Detector Engine to LlamaIndex through Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpLanguage Detector Engine + LlamaIndex FAQ
Common questions about integrating Language Detector Engine MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
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