A
licenseB
qualityD
maintenanceEnables MCP-compatible AI applications to translate text between languages with automatic language detection, contextual hints, custom instructions, and multi-language support.
1
1,539 npm
MIT
Lara Translate MCP Server
by ACRT-EVAL
Related Servers
Alternatives to Lara Translate MCP Server
No user-submitted related servers found.
Related Servers
- AlicenseBqualityDmaintenanceEnables AI applications to perform multi-language translations with automatic language detection, contextual hints, and custom instructions through an MCP-compatible interface.11,539 npmMIT
- AlicenseAqualityDmaintenanceEnables MCP-compatible AI applications to translate text through the Lara Translate API, with automatic language detection, context-aware translations, and custom instructions.11,539 npmMIT
- AlicenseBqualityDmaintenanceEnables AI applications to perform text translation across numerous language pairs with automatic source-language detection, contextual hints, and custom instructions.11,539 npmMIT
- AlicenseAqualityCmaintenanceEnables translation of single texts or batches through Google or user-supplied AI providers, with engine listing and configuration from any MCP client.3377 npmMIT
- AlicenseNot gradedqualityDmaintenanceAn AI-driven text translation service supporting 20+ languages, based on the Model Context Protocol (MCP) for integration with Claude Desktop and other MCP-compatible applications.MIT
TDQS
B3.4/5.0
Scored across 1 tool
Disambiguation5/5
With only a single tool, there is no possibility of confusing it with another operation. The tool's purpose is unambiguous: translate text between languages.
Naming Consistency5/5
The lone name 'translate' is a clear, conventional verb that matches the server's single responsibility. There is no mixed convention to worry about.
Tool Count3/5
One tool is on the thin side for a translation service, which commonly exposes related operations like language listing or batch translation. Still, the surface is focused and not bloated.
Completeness3/5
Translation itself is covered, including detection and context, but there are notable gaps: no way to list supported languages, no separate detection endpoint, and no batch or glossary management. Agents can still accomplish the core task but may hit dead ends for discovery.
Maintenance
ActivityInactive
ResponsivenessNo issues