{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"smithery_erlio-invezgo","slug":"erlio-invezgo","name":"invezgo","type":"mcp","url":"https://smithery.ai/servers/erlio/invezgo","page_url":"https://unfragile.ai/erlio-invezgo","categories":["mcp-servers"],"tags":["mcp","model-context-protocol","smithery:erlio/invezgo"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"smithery_erlio-invezgo__cap_0","uri":"capability://tool.use.integration.multi.provider.model.context.orchestration","name":"multi-provider model context orchestration","description":"Invezgo leverages a model-context-protocol (MCP) architecture to seamlessly integrate multiple AI models and APIs, allowing for dynamic context switching based on user queries. This is achieved through a centralized orchestration layer that manages requests, ensuring that the most relevant model is utilized for each specific task. The design supports extensibility, enabling easy addition of new models or APIs without disrupting existing workflows.","intents":["How can I integrate multiple AI models into my application?","I need to switch between different AI services based on user input.","What is the best way to manage context across various AI models?"],"best_for":["developers building applications that require multi-model AI integration"],"limitations":["Performance may degrade with more than three concurrent model integrations due to increased context switching overhead."],"requires":["Node.js 14+","API keys for integrated models"],"input_types":["text","structured data"],"output_types":["text","structured data"],"categories":["tool-use-integration","mcp-servers"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_erlio-invezgo__cap_1","uri":"capability://data.processing.analysis.contextual.data.transformation","name":"contextual data transformation","description":"Invezgo supports contextual data transformation by applying specific transformation rules based on the active model's requirements. This is achieved through a rule-based engine that interprets incoming data and adjusts it to fit the expected input format of the selected AI model, ensuring compatibility and optimizing performance.","intents":["How can I transform data to fit different AI model requirements?","What is the best way to prepare input data for various AI services?","Can I automate data formatting based on the model in use?"],"best_for":["data engineers working with multiple AI models"],"limitations":["Transformation rules must be manually defined, which can be time-consuming."],"requires":["Node.js 14+","Defined transformation rules for each model"],"input_types":["structured data"],"output_types":["structured data"],"categories":["data-processing-analysis","mcp-servers"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_erlio-invezgo__cap_2","uri":"capability://tool.use.integration.dynamic.api.integration.management","name":"dynamic api integration management","description":"Invezgo features a dynamic API integration management system that allows developers to easily add, remove, or update API integrations without requiring extensive code changes. This is facilitated by a plugin architecture that abstracts the API interaction layer, enabling developers to focus on functionality rather than integration details.","intents":["How can I quickly add new AI services to my application?","What is the easiest way to manage API integrations in my project?","Can I update API endpoints without redeploying my application?"],"best_for":["developers looking for flexible API management solutions"],"limitations":["Requires a solid understanding of the plugin architecture for effective use."],"requires":["Node.js 14+","Basic knowledge of plugin development"],"input_types":["text","structured data"],"output_types":["text","structured data"],"categories":["tool-use-integration","mcp-servers"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":28,"verified":false,"data_access_risk":"moderate","permissions":["Node.js 14+","API keys for integrated models","Defined transformation rules for each model","Basic knowledge of plugin development"],"failure_modes":["Performance may degrade with more than three concurrent model integrations due to increased context switching overhead.","Transformation rules must be manually defined, which can be time-consuming.","Requires a solid understanding of the plugin architecture for effective use.","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.16,"ecosystem":0.38999999999999996,"match_graph":0.25,"freshness":0.9,"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":"2026-05-24T12:16:26.346Z","last_scraped_at":"2026-05-03T15:19:34.640Z","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=erlio-invezgo","compare_url":"https://unfragile.ai/compare?artifact=erlio-invezgo"}},"signature":"/ZK5g9aXrLuKQbsmH95QwWbkzcjgKcsL2JI0fIlGSWabFaXwemAUNKPvTdjG0iWQZMmixBQP+/g/5UGRkgKnBA==","signedAt":"2026-06-18T00:02:05.571Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/erlio-invezgo","artifact":"https://unfragile.ai/erlio-invezgo","verify":"https://unfragile.ai/api/v1/verify?slug=erlio-invezgo","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"}}