Once connected, your AI assistant can manage your entire localization engine configuration through natural language. This page lists every capability exposed through the MCP server.
Engine management#
Create, update, and inspect localization engines. Each engine is an independent configuration scope with its own models, glossary, brand voice, and instructions.
Brand voice#
Define how your product speaks in each locale. Set formal German ("Sie"), informal Italian ("tu"), or any per-locale tone. Your assistant can create, update, and remove brand voice profiles directly.
Glossary#
Add terms that must be localized exactly - or not localized at all. When you tell your assistant "make sure '911' localizes to '112' in German," it creates the glossary entry immediately. Glossary entries are matched during localization via semantic similarity, so exact phrasing in source content doesn't need to match the glossary entry verbatim.
Instructions#
Encode linguistic rules that generic models miss. Space before percentage signs in French, adjective positioning in Spanish, pronoun formality per market. Your assistant adds these as locale-scoped instructions that apply to every localization.
LLM model configuration#
Configure which model handles each locale pair, with ranked fallbacks. Assign Claude for European languages, GPT for CJK, or any combination - your assistant manages the full model routing table.
AI Reviewers#
Create and configure AI Reviewers that automatically evaluate localization quality. Define review criteria, select the evaluation model, and set sampling rates. Attach or detach scorers from specific engines.
Localization#
Run localizations directly through your engine - single requests with full context enrichment, or async batch jobs targeting up to 100 locales in one call. Also detect the language of arbitrary text. See Localize from the Editor for detailed workflows.
Observability#
Inspect request logs with full execution context - which model handled a request, token usage, duration, fallback status, and complete input/output. Retrieve AI Reviewer verdicts, glossary compliance reports, and instruction adherence results per request. See Debug Localization Quality for the post-mortem workflow.
Engine provisioning#
Submit links and content to create a fully configured engine automatically - AI extracts brand voice, glossary terms, and instructions from your sources. See Provision Engines with AI for details.
Available models#
List all LLM models available for assignment to your engine's model chains. Your assistant can query this to know what options exist before configuring a locale pair.
API keys#
Generate and revoke API keys for programmatic access to your localization engine.
Integration credentials#
Manage credentials for external integrations connected to your organization.
Permissions and roles#
Manage role-based access control from the conversation: list roles and permissions, create custom roles, assign users to roles, manage per-engine access grants, and transfer organization ownership.
Audit logs#
Query the append-only history of state-changing actions in your organization - who changed what, when, from which IP. Filter by actor, target, action type, or time range.
AI agent threads#
Create and manage AI agent threads for automated localization debugging and issue resolution.