{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"smithery_yujaeyun-learnlog-mcp","slug":"yujaeyun-learnlog-mcp","name":"learnlog-mcp","type":"mcp","url":"https://github.com/YUJAEYUN/learnlog-mcp","page_url":"https://unfragile.ai/yujaeyun-learnlog-mcp","categories":["mcp-servers"],"tags":["mcp","model-context-protocol","smithery:yujaeyun/learnlog-mcp"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"smithery_yujaeyun-learnlog-mcp__cap_0","uri":"capability://tool.use.integration.mcp.server.integration.for.model.context.management","name":"mcp server integration for model context management","description":"This capability allows seamless integration with various machine learning models by adhering to the Model Context Protocol (MCP). It uses a modular architecture that enables dynamic loading of model adapters, allowing developers to easily switch between models without altering the core server logic. This design choice enhances flexibility and scalability, making it distinct in its ability to support multiple model types concurrently.","intents":["How can I integrate multiple ML models into my application using a single server?","What is the best way to manage context for different machine learning models?","Can I switch models dynamically without restarting my server?"],"best_for":["developers building applications that require multiple ML model integrations"],"limitations":["Performance may degrade with too many active models due to resource contention","Limited documentation on custom model adapter creation"],"requires":["Node.js 14+","Access to compatible ML models"],"input_types":["model requests","context data"],"output_types":["model responses","context updates"],"categories":["tool-use-integration","model-management"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_yujaeyun-learnlog-mcp__cap_1","uri":"capability://memory.knowledge.contextual.data.storage.and.retrieval","name":"contextual data storage and retrieval","description":"This capability provides a mechanism for storing and retrieving contextual data associated with model interactions. It employs a key-value store pattern, where each model interaction can be linked to specific context identifiers, allowing for efficient retrieval and management of context data. This approach ensures that the server can maintain state across different user sessions and model invocations.","intents":["How can I store user-specific context for ML model interactions?","What is the best way to retrieve context data for a specific user session?","Can I manage state across multiple model invocations?"],"best_for":["developers needing to maintain user context in ML applications"],"limitations":["No built-in persistence; requires external storage solutions for long-term data retention","Limited scalability for high-volume context data"],"requires":["Redis or similar key-value store for context management"],"input_types":["context data","user identifiers"],"output_types":["context retrieval responses","status updates"],"categories":["memory-knowledge","context-management"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_yujaeyun-learnlog-mcp__cap_2","uri":"capability://tool.use.integration.dynamic.model.adapter.registration","name":"dynamic model adapter registration","description":"This capability allows developers to register new model adapters at runtime, facilitating the integration of custom or third-party ML models without server downtime. It leverages an event-driven architecture where new adapters can emit events that the server listens for, dynamically updating its available model list. This feature enhances the server's adaptability and responsiveness to changing requirements.","intents":["How can I add new ML models to my server without downtime?","What is the process for integrating third-party model adapters?","Can I customize model behavior dynamically?"],"best_for":["developers integrating custom ML models into existing applications"],"limitations":["Requires careful management of adapter lifecycle to avoid memory leaks","Limited support for complex adapter configurations"],"requires":["Node.js 14+","Knowledge of MCP specifications for adapter development"],"input_types":["adapter configuration data"],"output_types":["status messages","adapter availability updates"],"categories":["tool-use-integration","model-management"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":26,"verified":false,"data_access_risk":"moderate","permissions":["Node.js 14+","Access to compatible ML models","Redis or similar key-value store for context management","Knowledge of MCP specifications for adapter development"],"failure_modes":["Performance may degrade with too many active models due to resource contention","Limited documentation on custom model adapter creation","No built-in persistence; requires external storage solutions for long-term data retention","Limited scalability for high-volume context data","Requires careful management of adapter lifecycle to avoid memory leaks","Limited support for complex adapter configurations","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.16,"ecosystem":0.48999999999999994,"match_graph":0.25,"freshness":0.6,"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":"2026-05-24T12:16:28.695Z","last_scraped_at":"2026-05-03T15:19:46.451Z","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=yujaeyun-learnlog-mcp","compare_url":"https://unfragile.ai/compare?artifact=yujaeyun-learnlog-mcp"}},"signature":"dOML5/x/adm/vB1m82ctKiXVxwY9NtDTzyuz1MPaU8oAEjjybvJngaip2oL6tCh+Q51mnE82oO8ltZq3BOMvCw==","signedAt":"2026-06-20T09:29:37.544Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/yujaeyun-learnlog-mcp","artifact":"https://unfragile.ai/yujaeyun-learnlog-mcp","verify":"https://unfragile.ai/api/v1/verify?slug=yujaeyun-learnlog-mcp","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"}}