Language Detection Skill

What this skill does

Give your agent language detection. Call it as an MCP tool to identify the language of any text and return its name and ISO code. You switch it on with a single toggle — no SDK and no endpoint wiring — and it answers over MCP or REST using the same key as every other skill.

See it work

A real response from the Language Detection Skill — exactly what your agent gets back when it makes the call.

vervekit · textlanguagetool call

{
  "text": "Ceci est un exemple de texte. Il peut détecter la langue"
}

result

language: french
iso: fr

Run it with your own input. Live calls happen in your dashboard, on your key.

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Ways to use it

Text tooling without the ML stack

Enable Language Detection and your app can detect language — translate, analyze, clean — without hosting a model or wiring a language API.

A tool your agent invokes

Over MCP, textlanguage is the tool your model calls to process text mid-task, on the same connection as every other skill.

Batch it from your backend

Call Language Detection over REST to detect language across a whole queue of text in your own server-side job.

Use it in your app

Once enabled, this skill is reachable two ways — pick whichever fits how you build. Both use the same key.

For AI agentsMCP

It appears to your model as a callable tool. No extra code — the agent invokes it when a task needs it.

textlanguage

For apps & backendsREST

Call it from your server with one request and your key. Node, Python, Go — anything that can send a GET.

GET /v1/textlanguage

Ask your agent

“Enable Language Detection and ask your agent to detect language.”
“Clean this text up and tell me what's in it.”

Language Detection Skill, answered

How to connect it over MCP or REST.

How do I add Language Detection to my app or agent?

Enable the Language Detection Skill on VerveKit, then reach it two ways with the same key: over MCP (it appears to your agent as the textlanguage tool) or over REST (call it from any backend). No SDK to install and no endpoint to wire.

MCP or REST — which should I use?

Both work off one key. Use MCP when an AI agent should decide when to detect language — the skill shows up as a callable tool. Use REST when your own server-side code should call it directly. Many apps use both.

Which agents and frameworks does it work with?

Any MCP client — Claude, Cursor, LangChain, and custom agents all speak the Model Context Protocol, so Language Detection appears as a standard tool with nothing skill-specific to integrate.

How many credits does a Language Detection call cost?

Each call costs 1 credit. Every skill rides the same key and the same connection, so enabling more skills doesn't add more integrations to manage.

Do I need to install anything?

No SDK and no endpoint wiring — enabling the skill is a toggle. You point your agent at the VerveKit MCP endpoint (or call REST) and Language Detection is available immediately.

Where does the data come from, and what shows on my bill?

VerveKit runs on APIVerve, our production data engine; Language Detection is one of 300+ skills on the same key. Invoices and card statements show APIVERVE.

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Text tooling without the ML stack

A tool your agent invokes

Batch it from your backend

Language Detection Skill, answered

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