Lokalise MCP Server
MCP ServerFreeConnect AI assistants to Lokalise to manage translation projects, keys, and workflows through natural conversation. Automate localization tasks, monitor progress, and collaborate with your team without writing code. Streamline your translation management directly from your chat interface.
Capabilities8 decomposed
natural language translation project management via mcp
Medium confidenceExposes Lokalise translation projects as MCP tools that AI assistants can invoke through natural conversation. Uses the Model Context Protocol to register project management operations (create, read, update, delete projects) as callable functions with structured schemas, allowing assistants to parse user intent from chat and execute API calls to Lokalise's REST backend without the user writing code.
Implements MCP tool registration pattern to expose Lokalise project operations as first-class callable functions within AI assistant conversations, bridging the gap between natural language intent and structured API calls without requiring users to write integration code.
Enables conversational project management directly in AI assistants (vs. requiring manual API calls or custom integrations), reducing friction for non-technical users while maintaining full programmatic control for developers.
translation key crud operations through conversational interface
Medium confidenceProvides MCP tools for creating, reading, updating, and deleting translation keys within Lokalise projects. The server translates natural language requests (e.g., 'add a new key for the login button') into structured API calls that manage the key registry, including metadata like context, character limits, and pluralization rules. Uses schema-based tool definitions to enforce valid key structures and project context.
Implements schema-based key validation within MCP tool definitions, ensuring that conversational requests for key creation/updates conform to Lokalise's key structure requirements (naming conventions, metadata fields) before API submission.
Allows developers to manage translation keys through natural conversation (vs. manual UI entry or raw API calls), reducing context-switching and enabling integration with AI-driven content workflows.
translation progress monitoring and status reporting
Medium confidenceExposes MCP tools that query Lokalise project statistics and translation completion metrics, returning structured data about language coverage, translator activity, and key translation status. The server aggregates data from Lokalise's analytics endpoints and formats it for conversational consumption, allowing assistants to answer questions like 'What's our translation progress for German?' without requiring users to log into the dashboard.
Aggregates multi-dimensional translation metrics (completion %, translator activity, key status) into a single MCP tool that formats data for conversational readability, bridging the gap between raw API statistics and human-friendly reporting.
Enables real-time progress queries through chat (vs. logging into dashboards or running manual API queries), making translation status visible to non-technical stakeholders.
batch translation workflow automation
Medium confidenceProvides MCP tools for orchestrating multi-step translation workflows, such as uploading new strings, assigning them to translators, and triggering review cycles. The server chains multiple Lokalise API calls based on conversational instructions, managing state across operations (e.g., remembering which keys were just created to assign them to a translator). Uses MCP's tool composition pattern to decompose complex workflows into atomic steps.
Implements workflow orchestration by chaining MCP tool calls across multiple Lokalise API endpoints, maintaining conversational context to track state and dependencies between operations without requiring external workflow engines.
Automates multi-step translation workflows through natural conversation (vs. manual UI steps or custom scripts), reducing operational overhead and enabling non-developers to orchestrate complex localization processes.
team collaboration and permission management via chat
Medium confidenceExposes MCP tools for managing team members, roles, and permissions within Lokalise projects. Allows assistants to add/remove team members, assign translator roles, and configure access levels through conversational commands. The server translates natural language role descriptions ('make Alice a German translator') into structured API calls that update Lokalise's team and permission model.
Maps natural language role descriptions to Lokalise's permission model, automatically resolving language assignments and role hierarchies without requiring users to understand the underlying permission structure.
Enables conversational team management (vs. manual UI configuration or API calls), reducing friction for non-technical team leads and enabling automated provisioning workflows.
multilingual content synchronization and versioning
Medium confidenceProvides MCP tools for syncing translation content across multiple Lokalise projects or language variants, and managing version history. The server can copy translations between projects, create language variants, and retrieve historical versions of keys/translations. Uses Lokalise's branching and version APIs to maintain consistency across localization variants without manual duplication.
Implements cross-project synchronization logic that maps keys and translations between Lokalise projects, enabling variant management and staged rollouts without requiring external ETL tools.
Automates multilingual content sync through conversation (vs. manual copy-paste or custom scripts), reducing errors and enabling non-developers to manage complex localization variants.
context-aware translation suggestions and quality checks
Medium confidenceExposes MCP tools that leverage Lokalise's translation memory and AI-powered suggestions to recommend translations for new keys based on existing translations and context. The server queries Lokalise's suggestion engine and formats recommendations for conversational consumption. Can also run quality checks (terminology consistency, length validation, placeholder matching) on translations and report issues through the chat interface.
Integrates Lokalise's translation memory and suggestion engine into MCP tools, enabling AI assistants to provide context-aware translation recommendations and automated quality validation without requiring external ML models.
Provides conversational access to translation suggestions and QA checks (vs. manual review or separate QA tools), improving translation consistency and reducing review cycles.
integration with external localization services and workflows
Medium confidenceProvides MCP tools that connect Lokalise to external services (e.g., translation agencies, CAT tools, content management systems) through API orchestration. The server can export translations to external formats, import translations from other sources, and trigger webhooks for downstream workflows. Uses MCP's tool composition to chain Lokalise operations with external API calls.
Implements multi-service orchestration through MCP, allowing AI assistants to coordinate Lokalise operations with external localization tools and workflows without requiring custom integration code.
Enables conversational orchestration of multi-tool localization workflows (vs. manual data export/import or custom scripts), reducing integration complexity and enabling non-developers to manage complex pipelines.
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
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Best For
- ✓Product teams using Claude or other MCP-compatible AI assistants for localization workflows
- ✓Non-technical project managers who want to manage translations via chat
- ✓Developers building AI agents that need to orchestrate localization tasks
- ✓Development teams managing large translation key inventories
- ✓Localization managers who need to bulk-update key metadata
- ✓CI/CD pipelines that need to programmatically sync keys from code to Lokalise
- ✓Project managers tracking localization timelines
- ✓Team leads monitoring translator productivity
Known Limitations
- ⚠Requires MCP-compatible AI assistant (Claude, or custom implementations) — not usable with standard ChatGPT
- ⚠Project operations are limited to CRUD; complex workflows require multiple conversation turns
- ⚠No real-time project synchronization — changes made outside the assistant won't auto-refresh in conversation context
- ⚠Bulk operations are limited by MCP message size constraints — very large key batches (1000+) may require pagination
- ⚠No built-in key validation against codebase — keys can be created that don't exist in source code
- ⚠Metadata updates (context, character limits) don't automatically propagate to existing translations
Requirements
Input / Output
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Connect AI assistants to Lokalise to manage translation projects, keys, and workflows through natural conversation. Automate localization tasks, monitor progress, and collaborate with your team without writing code. Streamline your translation management directly from your chat interface.
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