{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"npm_npm-deepl-mcp-server","slug":"npm-deepl-mcp-server","name":"deepl-mcp-server","type":"mcp","url":"https://www.npmjs.com/package/deepl-mcp-server","page_url":"https://unfragile.ai/npm-deepl-mcp-server","categories":["mcp-servers"],"tags":["deepl","mcp","translation","claude","ai"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"npm_npm-deepl-mcp-server__cap_0","uri":"capability://tool.use.integration.mcp.native.deepl.translation.with.claude.integration","name":"mcp-native deepl translation with claude integration","description":"Exposes DeepL's translation API as an MCP server resource, allowing Claude and other MCP clients to invoke translations through standardized tool-calling protocols. Implements the Model Context Protocol specification to register translation as a callable tool with schema-based parameter validation, enabling Claude to translate text within multi-turn conversations without external API calls from the client.","intents":["I want Claude to translate text in real-time during conversations without me managing API keys or making separate requests","I need to build an AI agent that can translate content as part of a larger workflow","I want to use DeepL's translation quality within Claude's reasoning context"],"best_for":["AI developers building Claude-based agents that need translation capabilities","Teams integrating DeepL into MCP-compatible AI workflows","Builders prototyping multilingual AI applications with Claude"],"limitations":["Requires DeepL API key with active subscription or free tier account","MCP server must be running as a separate process — adds deployment complexity vs direct API calls","No built-in request batching — each translation call incurs separate API round-trip to DeepL","Limited to DeepL's supported language pairs — cannot extend with custom translation models"],"requires":["Node.js 16+ (typical MCP server requirement)","DeepL API key (free or paid tier)","MCP-compatible client (Claude Desktop, or custom MCP client implementation)","Network connectivity to DeepL API endpoints"],"input_types":["text (plain string)","structured JSON with text and language parameters"],"output_types":["translated text (string)","structured JSON with translation metadata (detected language, alternatives if available)"],"categories":["tool-use-integration","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-deepl-mcp-server__cap_1","uri":"capability://data.processing.analysis.language.detection.and.source.language.inference","name":"language detection and source-language inference","description":"Automatically detects the source language of input text and passes it to DeepL's API, eliminating the need for explicit language specification in most cases. Leverages DeepL's built-in language detection or implements client-side heuristics to infer language before translation, reducing user friction when language is unknown.","intents":["I want to translate text without specifying its source language","I need Claude to automatically detect what language a user is writing in before translating","I want to handle mixed-language inputs gracefully"],"best_for":["Conversational AI applications where users may switch languages unpredictably","Multilingual content processing pipelines","Developers building language-agnostic translation workflows"],"limitations":["Language detection accuracy depends on text length — short strings (< 20 characters) may be misidentified","Cannot reliably distinguish between similar languages (e.g., Norwegian vs Swedish) without explicit hints","Detection adds latency if implemented client-side before API call"],"requires":["DeepL API key with language detection support (available in most tiers)","Text input of sufficient length for reliable detection (20+ characters recommended)"],"input_types":["text (any language supported by DeepL)"],"output_types":["language code (ISO 639-1 or DeepL-specific code)","confidence score (if DeepL returns it)"],"categories":["data-processing-analysis","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-deepl-mcp-server__cap_2","uri":"capability://tool.use.integration.target.language.specification.with.fallback.handling","name":"target language specification with fallback handling","description":"Accepts target language parameters (ISO 639-1 codes or DeepL-specific language identifiers) and validates them against DeepL's supported language list before making API calls. Implements fallback logic to handle unsupported language requests gracefully, either by suggesting alternatives or defaulting to a configured language.","intents":["I want to translate to a specific language and get an error if it's not supported","I need to handle requests for unsupported languages without crashing the agent","I want Claude to suggest alternative languages when a requested language isn't available"],"best_for":["Multilingual applications with strict language requirements","Agents that need to validate user input before calling external APIs","Teams building resilient translation pipelines"],"limitations":["Fallback behavior must be configured at server startup — cannot be changed per-request","No built-in language similarity matching — cannot suggest 'closest' alternative language","DeepL's supported language list changes infrequently but requires manual updates to MCP server"],"requires":["DeepL API key","Knowledge of DeepL's current supported language codes"],"input_types":["language code (ISO 639-1 or DeepL format, e.g., 'en', 'de', 'pt-BR')"],"output_types":["validation result (boolean or error message)","list of supported languages (if requested)"],"categories":["tool-use-integration","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-deepl-mcp-server__cap_3","uri":"capability://automation.workflow.batch.translation.orchestration.via.mcp.tool.chaining","name":"batch translation orchestration via mcp tool chaining","description":"Enables Claude to translate multiple text segments in sequence by invoking the translation tool multiple times within a single conversation context. The MCP server maintains stateless request handling, allowing Claude to manage batch logic through its own planning and multi-turn reasoning rather than requiring server-side batch endpoints.","intents":["I want Claude to translate a list of sentences one by one and compile results","I need to translate document sections while Claude tracks progress and handles errors","I want Claude to parallelize translations by calling the tool multiple times concurrently"],"best_for":["Document translation workflows where Claude orchestrates the batching logic","Agents that need to translate variable-length content lists","Developers who want Claude's reasoning to drive batch processing decisions"],"limitations":["No server-side batching — each translation incurs separate DeepL API call and quota consumption","Claude's token context limits how many translations can be tracked in a single conversation","No built-in rate limiting — rapid batch calls may hit DeepL's rate limits","Requires Claude to manage batch state — no persistent batch tracking across sessions"],"requires":["DeepL API key with sufficient quota for multiple calls","MCP client (Claude) capable of multi-turn tool invocation","Sufficient token budget in Claude's context window"],"input_types":["text (multiple segments passed in sequence)"],"output_types":["translated text (one per tool invocation)","batch results compiled by Claude"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-deepl-mcp-server__cap_4","uri":"capability://memory.knowledge.translation.context.preservation.through.conversation.history","name":"translation context preservation through conversation history","description":"Leverages MCP's context passing and Claude's conversation memory to maintain translation context across multiple requests. Previous translations, language preferences, and domain-specific terminology can be referenced by Claude in subsequent translation requests, enabling more consistent and context-aware translations without explicit state management in the MCP server.","intents":["I want Claude to remember previous translations and maintain terminology consistency","I need translations to respect domain-specific glossaries mentioned earlier in the conversation","I want Claude to adapt translation style based on earlier examples"],"best_for":["Long-running translation sessions where consistency matters","Domain-specific translation (legal, medical, technical) where terminology must be consistent","Conversational agents that build translation context over time"],"limitations":["Context is limited to Claude's token window — very long conversations lose early translation history","No persistent glossary storage — terminology context is lost when conversation ends","DeepL API itself has no memory of previous translations — consistency depends entirely on Claude's reasoning","Requires Claude to explicitly reference previous translations — no automatic context injection"],"requires":["Claude model with sufficient context window (Claude 3.5 Sonnet or larger recommended)","Conversation history preserved in MCP client"],"input_types":["text (with implicit context from conversation history)"],"output_types":["translated text (informed by conversation context)"],"categories":["memory-knowledge","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-deepl-mcp-server__cap_5","uri":"capability://automation.workflow.streaming.translation.output.if.supported","name":"streaming translation output (if supported)","description":"If implemented, provides streaming translation results as they become available from DeepL's API, allowing Claude to process partial translations incrementally rather than waiting for complete results. Uses MCP's streaming capabilities or chunked response patterns to deliver translation output in real-time.","intents":["I want to see translation results as they arrive, not wait for the full response","I need to process large translations incrementally to reduce latency","I want Claude to start reasoning on partial translations while more content arrives"],"best_for":["Real-time translation interfaces where latency matters","Large document translation where streaming reduces perceived wait time","Agents processing streaming input that needs immediate translation"],"limitations":["DeepL API does not natively support streaming — implementation would require chunking or polling","Streaming adds complexity to MCP server implementation and client handling","Partial translations may be less accurate than full-context translations","Unknown if deepl-mcp-server actually implements streaming — likely not based on typical MCP patterns"],"requires":["MCP client with streaming support","DeepL API key (streaming not a standard feature)"],"input_types":["text (can be streamed or chunked)"],"output_types":["streamed translation chunks"],"categories":["automation-workflow","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-deepl-mcp-server__cap_6","uri":"capability://safety.moderation.deepl.api.error.handling.and.retry.logic","name":"deepl api error handling and retry logic","description":"Implements error handling for DeepL API failures (rate limits, network errors, invalid requests) and provides structured error responses to Claude through MCP's error protocol. May include automatic retry logic with exponential backoff for transient failures, allowing Claude to decide whether to retry or handle the error gracefully.","intents":["I want Claude to know when a translation fails and why","I need the translation tool to retry automatically on temporary failures","I want to handle rate limiting gracefully without crashing the agent"],"best_for":["Production agents that need resilience to API failures","Applications with high translation volume that may hit rate limits","Teams building fault-tolerant multilingual systems"],"limitations":["Retry logic must be configured at server startup — cannot be adjusted per-request","No built-in fallback to alternative translation services (e.g., Google Translate)","Rate limit handling depends on DeepL's rate limit headers — may not work with all account tiers","Exponential backoff may cause unacceptable delays in time-sensitive applications"],"requires":["DeepL API key","Network connectivity with reasonable timeout tolerances"],"input_types":["text (any valid input)"],"output_types":["translated text (on success)","error object with code and message (on failure)"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-deepl-mcp-server__cap_7","uri":"capability://tool.use.integration.mcp.resource.discovery.and.tool.schema.registration","name":"mcp resource discovery and tool schema registration","description":"Registers the translation capability as a discoverable MCP tool with JSON schema describing parameters (source language, target language, text content) and return types. Implements MCP's resource/tool discovery protocol so Claude and other MCP clients can introspect available translation options without hardcoding tool definitions.","intents":["I want Claude to automatically discover that translation is available without manual configuration","I need other MCP clients to understand what parameters the translation tool accepts","I want to update translation capabilities without modifying Claude's configuration"],"best_for":["Developers building MCP-compatible applications","Teams deploying multiple MCP servers that need dynamic tool discovery","Builders who want to avoid hardcoding tool schemas in client applications"],"limitations":["Schema registration is static at server startup — cannot dynamically add new translation options","MCP clients must support tool discovery — older or custom clients may not use schema registration","Schema changes require server restart — no hot-reloading of tool definitions"],"requires":["MCP-compatible client (Claude Desktop, custom MCP client)","Node.js 16+ with MCP server library"],"input_types":["none (discovery is metadata-driven)"],"output_types":["JSON schema describing translation tool parameters and return types"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":26,"verified":false,"data_access_risk":"moderate","permissions":["Node.js 16+ (typical MCP server requirement)","DeepL API key (free or paid tier)","MCP-compatible client (Claude Desktop, or custom MCP client implementation)","Network connectivity to DeepL API endpoints","DeepL API key with language detection support (available in most tiers)","Text input of sufficient length for reliable detection (20+ characters recommended)","DeepL API key","Knowledge of DeepL's current supported language codes","DeepL API key with sufficient quota for multiple calls","MCP client (Claude) capable of multi-turn tool invocation"],"failure_modes":["Requires DeepL API key with active subscription or free tier account","MCP server must be running as a separate process — adds deployment complexity vs direct API calls","No built-in request batching — each translation call incurs separate API round-trip to DeepL","Limited to DeepL's supported language pairs — cannot extend with custom translation models","Language detection accuracy depends on text length — short strings (< 20 characters) may be misidentified","Cannot reliably distinguish between similar languages (e.g., Norwegian vs Swedish) without explicit hints","Detection adds latency if implemented client-side before API call","Fallback behavior must be configured at server startup — cannot be changed per-request","No built-in language similarity matching — cannot suggest 'closest' alternative language","DeepL's supported language list changes infrequently but requires manual updates to MCP server","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.26,"ecosystem":0.45,"match_graph":0.25,"freshness":0.52,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:23.903Z","last_scraped_at":"2026-04-22T08:09:30.559Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=npm-deepl-mcp-server","compare_url":"https://unfragile.ai/compare?artifact=npm-deepl-mcp-server"}},"signature":"goN4zcm3IScfXNBk6DN8PzbsTS2kGlV8Udc9IhcXx/24sorqu97c9ZsxX/6AJFo4zIl+phExWgo31VaGQ6qWBA==","signedAt":"2026-06-23T06:37:43.053Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/npm-deepl-mcp-server","artifact":"https://unfragile.ai/npm-deepl-mcp-server","verify":"https://unfragile.ai/api/v1/verify?slug=npm-deepl-mcp-server","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}