Bring N Gram Analysis
to Vercel AI SDK
Learn how to connect Language Detector Engine to Vercel AI SDK and start using 1 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
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 Vercel AI SDK?
The Vercel AI SDK gives every Language Detector Engine tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 1 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
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TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
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Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Language Detector Engine integration everywhere
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Built-in streaming UI primitives let you display Language Detector Engine tool results progressively in React, Svelte, or Vue components
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Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
Language Detector Engine in Vercel AI SDK
Language Detector Engine and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Language Detector Engine to Vercel AI SDK 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 Vercel AI SDK
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 Vercel AI SDK 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 Vercel AI SDK
Every tool call from Vercel AI SDK 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 the Vercel AI SDK connect to MCP servers?
Import createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.
Can I use MCP tools in Edge Functions?
Yes. The AI SDK is fully edge-compatible. MCP connections work on Vercel Edge Functions, Cloudflare Workers, and similar runtimes.
Does it support streaming tool results?
Yes. The SDK provides streaming primitives like useChat and streamText that handle tool calls and display results progressively in the UI.
createMCPClient is not a function
Install: npm install @ai-sdk/mcp
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