franc Connector for AI agents.
1 live capability
Identify languages with deterministic accuracy for support routing
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Why people use franc
Language Detector Engine for Accurate Support Routing
With this Connector, your AI agent identifies the language instantly. It routes the ticket to the correct team automatically, saving your staff from manual sorting.
What Vinkius changes
The Language Detector Engine provides deterministic results for multi-lingual data.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,100+ Connectors
- Real-world use case 01
Support Ticket Routing
A customer sends a message in Portuguese.
- Real-world use case 02
Content Moderation
A system scans posts in 50 different countries.
- Real-world use case 03
Data Cleaning
A dataset has mixed languages.
Complete set · 1capability
The complete franc capability set.
These are the exact actions your AI can choose when you ask it to work with franc.
01
1 capability in this set.
Part of 1 available through franc.
- 01 Capability
Detect language
Identify the language of a text string and get the ISO 639-3 code. The Language Detector Engine works across 400+ languages using deterministic math to ensure consistent results.
Set up in minutes
One URL. Then ask franc to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use franc from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_DZfpdhfq3SUunsFFJJgaaLCPk3BDMKLefzz6agcr/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it franc, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable franc for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_DZfpdhfq3SUunsFFJJgaaLCPk3BDMKLefzz6agcr/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the franc URL.
- Step 03
Save and start
Save the connection and enable franc in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"language-detector-engine": {
"url": "https://edge.vinkius.com/vk_preview_DZfpdhfq3SUunsFFJJgaaLCPk3BDMKLefzz6agcr/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using franc
Open Agent mode in chat and ask: "Using franc, help me...". 1 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"language-detector-engine": {
"url": "https://edge.vinkius.com/vk_preview_DZfpdhfq3SUunsFFJJgaaLCPk3BDMKLefzz6agcr/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using franc
Ask Copilot: "Using franc, help me...". 1 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"language-detector-engine": {
"url": "https://edge.vinkius.com/vk_preview_DZfpdhfq3SUunsFFJJgaaLCPk3BDMKLefzz6agcr/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using franc
Open Cascade and ask: "Using franc, help me...". 1 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"language-detector-engine": {
"url": "https://edge.vinkius.com/vk_preview_DZfpdhfq3SUunsFFJJgaaLCPk3BDMKLefzz6agcr/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using franc
Ask Cline: "Using franc, help me...". 1 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add language-detector-engine --transport http "https://edge.vinkius.com/vk_preview_DZfpdhfq3SUunsFFJJgaaLCPk3BDMKLefzz6agcr/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using franc
Ask Claude: "Using franc, show me...". 1 tools are ready
Where the request belongs
Work franc can move forward.
The Language Detector Engine is for anyone handling high-volume, multi-lingual data where a wrong language guess causes real-world problems like broken routing or failed localization.
Support Operations Manager
Routes incoming tickets to the correct regional teams automatically to reduce response times.
Localization Engineer
Validates that content is being served in the correct language across different global markets.
Data Scientist
Cleans and categorizes multi-lingual datasets for training or analysis by filtering out noise.
Build the capability set
Add more capabilities.
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Localization Readiness Checker
Identify linguistic, cultural, and structural risks in your source text to ensure high-quality localization.
MeaningCloud
Advanced text analytics for sentiment analysis, topic extraction, language detection, and automatic summarization.
MonkeyLearn
Automate text analysis via MonkeyLearn. classify sentiment, extract keywords, and run custom NLP pipelines directly from any AI agent.
Bring your own AI
Change the model, client or framework. Keep franc connected.
-
Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
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Roo Code -
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Chorus -
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LangChain -
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CrewAI -
Vercel AI SDK
Before you connect
Questions about franc.
The practical details behind the request, access and result.
How does the Language Detector Engine handle short text?
The Language Detector Engine uses n-gram analysis to identify languages even in short strings. If the text is too short to be certain, it returns an undefined status to prevent incorrect guesses.
Can the Language Detector Engine identify rare languages?
Yes, it supports over 400 languages. This includes common global languages as well as less common regional dialects and languages like Zulu or Esperanto.
What happens if the Language Detector Engine can't find a match?
If the input is too ambiguous or doesn't match any known patterns, the Language Detector Engine returns 'undefined'. This ensures your AI agent doesn't hallucinate a language.
Does the Language Detector Engine support Spanish and Portuguese?
Yes, the Language Detector Engine identifies both Spanish and Portuguese accurately, providing standard ISO 639-3 codes for both.
How accurate is the Language Detector Engine for mixed text?
The Language Detector Engine analyzes character frequencies to handle mixed content. It can identify the primary language even when multiple languages appear in the same string.
Can I limit the Language Detector Engine to specific languages?
Yes, you can use a whitelist to force the Language Detector Engine to only look for specific codes. This is ideal for businesses that only support a few specific regions.
How does the Language Detector Engine help with support tickets?
It identifies the language of incoming tickets instantly. This allows your AI agent to route messages to the correct regional team without manual intervention.
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.
One connection away
Give your agent a direct line to franc.
Connect franc once. Keep it beside 6,100+ managed Connectors when the next task needs more.
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