Lara Translate MCP Server implements the Model Context Protocol to expose Lara Translate's translation capabilities to AI applications via MCP. It enables tool and resource discovery, request validation, and transformation of translation requests into Lara Translate API calls, with results returned to MCP clients. The server offers a Translation tool (translate) that translates an array of text blocks, where each block can be flagged as translatable, and supports optional source language, target language, context, instructions, and a source_hint to improve detection. The translation results preserve the original structure. In addition, the server provides a robust Translation Memories toolkit, including list_memories, create_memory, update_memory, delete_memory, add_translation, delete_translation, and import_tmx for loading TMX data. The TMX import workflow can also be monitored via check_import_status. This MCP integration enables AI applications to access Lara Translate's domain-aware translations without exposing credentials, and to adjust translation behavior through context, instructions, and domain-specific memories. The architecture emphasizes non-English language quality, parallel processing, and cost efficiency by pre-processing translations before engaging language models.