Compatible with every major AI agent and IDE
What is the 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.
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.
Built-in capabilities (1)
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")
Why Google ADK?
Google ADK natively supports Language Detector Engine as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 1 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.
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Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution
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Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Language Detector Engine
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Production-ready features like session management, evaluation, and deployment come built-in. not bolted on
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Seamless integration with Google Cloud services means you can combine Language Detector Engine tools with BigQuery, Vertex AI, and Cloud Functions
Language Detector Engine in Google ADK
Language Detector Engine and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Language Detector Engine to Google ADK through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Language Detector Engine in Google ADK
The Language Detector Engine 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. All 1 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Google ADK only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.

* 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
How Vinkius secures
Language Detector Engine for Google ADK
Every tool call from Google ADK to the Language Detector Engine MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Why is this better than asking Claude to detect the language?
LLMs often hallucinate languages for short strings or names. They also struggle to provide standardized ISO codes reliably. This engine uses mathematical N-gram analysis (the same technique behind Google Search language detection) to deterministically map text to one of 400+ ISO 639-3 codes.
What does it mean if it returns 'und'?
'und' stands for Undefined. It means the text is too short, mostly numbers, or too ambiguous to confidently map to a single language. This is a feature — it prevents your routing logic from making false assumptions.
Can I force it to choose between specific languages?
Yes. Pass an array of ISO 639-3 codes to the 'only' parameter (e.g., ['eng', 'por', 'spa']). The engine will only calculate probabilities within that subset.
How does Google ADK connect to MCP servers?
Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.
Can ADK agents use multiple MCP servers?
Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.
Which Gemini models work best with MCP tools?
Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.
McpToolset not found
Update: pip install --upgrade google-adk
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