{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"npm_npm-mcp-usecli","slug":"npm-mcp-usecli","name":"@mcp-use/cli","type":"cli","url":"https://www.npmjs.com/package/@mcp-use/cli","page_url":"https://unfragile.ai/npm-mcp-usecli","categories":["mcp-servers"],"tags":["mcp","model-context-protocol","cli","build-tool","widget","ui","react","esbuild","bundler","typescript"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"npm_npm-mcp-usecli__cap_0","uri":"capability://automation.workflow.mcp.server.scaffolding.and.project.initialization","name":"mcp server scaffolding and project initialization","description":"Generates boilerplate MCP server projects with TypeScript/JavaScript templates, pre-configured build pipelines, and dependency management. Uses esbuild-based bundling configuration and React component support for UI-driven MCP servers. Handles project structure creation, tsconfig setup, and package.json generation with appropriate MCP SDK dependencies.","intents":["I need to quickly bootstrap a new MCP server without manually configuring build tools and dependencies","I want to create an MCP server with React-based UI components for ChatGPT Apps integration","I need a standardized project structure that follows MCP best practices"],"best_for":["developers building their first MCP server","teams standardizing on MCP server development patterns","rapid prototyping of tool integrations for ChatGPT"],"limitations":["Limited to TypeScript/JavaScript — no Python or Go templates","Assumes esbuild as the bundler — no webpack or Vite alternatives","Generated projects require manual OAuth configuration if needed"],"requires":["Node.js 18+","npm or yarn package manager","Basic familiarity with MCP protocol concepts"],"input_types":["CLI arguments (project name, template type)"],"output_types":["directory structure","TypeScript source files","package.json with dependencies","build configuration files"],"categories":["automation-workflow","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-mcp-usecli__cap_1","uri":"capability://automation.workflow.mcp.server.build.and.bundling.with.esbuild","name":"mcp server build and bundling with esbuild","description":"Compiles and bundles MCP server source code using esbuild, handling TypeScript transpilation, dependency resolution, and output optimization. Manages separate entry points for different MCP transport mechanisms (stdio, SSE, WebSocket) and produces minified/sourcemapped artifacts. Integrates React component compilation for UI-driven servers.","intents":["I need to compile my TypeScript MCP server into production-ready JavaScript bundles","I want to optimize bundle size and build speed for rapid iteration during development","I need to generate separate bundles for different MCP transport protocols"],"best_for":["MCP server developers using TypeScript","teams with CI/CD pipelines requiring fast build times","developers building multi-transport MCP servers"],"limitations":["esbuild-only — no support for webpack or Rollup configurations","Tree-shaking effectiveness depends on ESM module structure in dependencies","No built-in code splitting for large monorepo MCP server collections"],"requires":["Node.js 18+","TypeScript 4.5+ (for type checking)","esbuild installed as dependency"],"input_types":["TypeScript source files","tsconfig.json configuration","package.json with entry points"],"output_types":["minified JavaScript bundles","source maps","compiled React components"],"categories":["automation-workflow","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-mcp-usecli__cap_10","uri":"capability://automation.workflow.multi.provider.mcp.server.deployment","name":"multi-provider mcp server deployment","description":"Manages deployment of MCP servers across multiple hosting providers (AWS, Google Cloud, Azure, Vercel, etc.) with provider-specific configuration and optimization. Handles environment setup, credential injection, and provider-specific deployment patterns (Lambda, Cloud Functions, serverless containers). Supports both serverless and traditional server deployments.","intents":["I want to deploy my MCP server to AWS Lambda without manual configuration","I need to deploy the same MCP server to multiple cloud providers with minimal changes","I want to optimize my MCP server deployment for a specific cloud provider's constraints"],"best_for":["teams deploying MCP servers to cloud platforms","developers requiring multi-cloud or hybrid deployments","organizations with existing cloud infrastructure"],"limitations":["Provider-specific optimizations require manual tuning per platform","Serverless deployments have cold start latency — not suitable for latency-critical tools","Credential management is provider-specific — no unified secret handling"],"requires":["cloud provider account and credentials","provider-specific CLI tools (AWS CLI, gcloud, etc.)","understanding of provider-specific deployment models"],"input_types":["MCP server code","provider configuration","deployment parameters"],"output_types":["deployed MCP server endpoint","deployment logs","provider-specific artifacts"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-mcp-usecli__cap_2","uri":"capability://tool.use.integration.chatgpt.apps.integration.and.deployment","name":"chatgpt apps integration and deployment","description":"Configures MCP servers for deployment as ChatGPT Apps with automatic manifest generation, OAuth credential handling, and notification endpoint setup. Manages the bridge between MCP protocol semantics and ChatGPT's tool/action model, including schema transformation and response formatting. Handles deployment to ChatGPT's app registry.","intents":["I want to expose my MCP server as a ChatGPT App without manually writing OpenAPI schemas","I need to configure OAuth flows for ChatGPT App authentication","I want to deploy my MCP server to ChatGPT's app marketplace"],"best_for":["developers building ChatGPT integrations","teams deploying MCP servers as consumer-facing ChatGPT Apps","OAuth-protected service providers"],"limitations":["ChatGPT App deployment requires OpenAI organization approval","OAuth configuration is manual — no automatic credential rotation","Limited to ChatGPT's supported authentication methods (OAuth 2.0 only)"],"requires":["OpenAI API key with ChatGPT Apps access","OAuth provider credentials (client ID, secret)","Valid MCP server endpoint (HTTP/HTTPS)"],"input_types":["MCP server schema","OAuth configuration","app metadata (name, description, icon)"],"output_types":["ChatGPT App manifest (JSON)","OpenAPI schema","deployment configuration"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-mcp-usecli__cap_3","uri":"capability://tool.use.integration.oauth.2.0.credential.management.and.token.refresh","name":"oauth 2.0 credential management and token refresh","description":"Manages OAuth 2.0 authentication flows for MCP servers, including authorization code exchange, token storage, and automatic refresh token rotation. Implements secure credential handling with environment variable injection and supports multiple OAuth providers. Integrates with MCP's context protocol to pass authenticated credentials to tools.","intents":["I need to authenticate my MCP server against third-party APIs using OAuth without managing tokens manually","I want to securely store and rotate OAuth credentials in my MCP server","I need to pass authenticated context to MCP tools for API calls"],"best_for":["MCP servers integrating with OAuth-protected APIs (Slack, GitHub, Google, etc.)","teams requiring secure credential management in production","developers building multi-tenant MCP servers"],"limitations":["Requires external credential storage — no built-in persistence (must use environment variables or external vault)","Token refresh logic is synchronous — high-latency OAuth providers may block tool execution","No support for PKCE or device flow — authorization code flow only"],"requires":["OAuth provider credentials (client ID, client secret)","Redirect URI registered with OAuth provider","Environment variable or secret management system"],"input_types":["OAuth provider configuration","authorization code from OAuth flow","refresh token"],"output_types":["access token","token metadata (expiration, scope)","authenticated context for MCP tools"],"categories":["tool-use-integration","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-mcp-usecli__cap_4","uri":"capability://tool.use.integration.server.sent.events.sse.transport.configuration","name":"server-sent events (sse) transport configuration","description":"Configures MCP servers to communicate via Server-Sent Events (SSE) protocol, enabling real-time bidirectional messaging over HTTP without WebSocket overhead. Handles connection lifecycle management, automatic reconnection, and message framing for MCP protocol semantics. Supports both client and server-side SSE endpoint setup.","intents":["I want to run my MCP server over HTTP/SSE instead of stdio for better browser compatibility","I need to configure automatic reconnection for MCP clients connecting via SSE","I want to deploy my MCP server behind a standard HTTP reverse proxy"],"best_for":["web-based MCP clients (browser extensions, web apps)","deployments behind HTTP load balancers","teams avoiding WebSocket complexity"],"limitations":["SSE is unidirectional (server-to-client) — requires separate HTTP POST channel for client-to-server messages","Higher latency than WebSocket due to HTTP overhead per message","Browser same-origin policy requires CORS configuration"],"requires":["HTTP server (Express, Fastify, etc.)","MCP client with SSE transport support","CORS configuration if client and server on different origins"],"input_types":["MCP messages (JSON)","HTTP request/response"],"output_types":["SSE stream (text/event-stream)","HTTP response"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-mcp-usecli__cap_5","uri":"capability://tool.use.integration.notifications.and.event.streaming","name":"notifications and event streaming","description":"Implements server-initiated notifications and event streaming for MCP servers, allowing servers to push updates to clients without request-response cycles. Manages notification subscriptions, event filtering, and delivery guarantees. Integrates with MCP's notification protocol to enable real-time updates for long-running operations or data changes.","intents":["I want my MCP server to push real-time updates to clients when data changes","I need to notify clients about long-running operation completion without polling","I want to implement event subscriptions where clients only receive relevant notifications"],"best_for":["MCP servers with real-time data sources (webhooks, message queues, databases)","applications requiring live updates (monitoring, collaboration tools)","teams building event-driven MCP architectures"],"limitations":["Notification delivery is best-effort — no built-in persistence for missed events","Requires stateful server — horizontal scaling needs shared event bus (Redis, etc.)","No built-in filtering — clients receive all subscribed events regardless of relevance"],"requires":["MCP client with notification support","event source (webhook, message queue, database trigger)","optional: message broker for multi-instance deployments"],"input_types":["event data (JSON)","subscription filters"],"output_types":["MCP notification messages","event stream"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-mcp-usecli__cap_6","uri":"capability://automation.workflow.sampling.and.request.batching","name":"sampling and request batching","description":"Implements request sampling and batching strategies for MCP servers to optimize throughput and reduce latency under high load. Handles request deduplication, batch aggregation, and response correlation. Useful for servers making expensive external API calls or database queries that benefit from batching.","intents":["I want to batch multiple MCP tool requests into a single external API call","I need to deduplicate identical concurrent requests to avoid redundant work","I want to implement request sampling to reduce load on expensive operations"],"best_for":["MCP servers integrating with rate-limited APIs","high-throughput deployments with expensive operations","teams optimizing database query patterns"],"limitations":["Batching adds latency (must wait for batch window) — not suitable for latency-critical operations","Sampling loses data — not appropriate for critical operations requiring 100% coverage","Requires careful tuning of batch size and window duration per use case"],"requires":["understanding of request patterns and external API constraints","configuration of batch size and time window parameters"],"input_types":["MCP tool requests","sampling configuration"],"output_types":["batched requests","correlated responses"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-mcp-usecli__cap_7","uri":"capability://automation.workflow.observability.and.structured.logging","name":"observability and structured logging","description":"Provides structured logging, tracing, and metrics collection for MCP servers with integration points for OpenTelemetry, Datadog, or other observability platforms. Captures request/response payloads, execution timing, error context, and tool invocation traces. Supports log levels, sampling, and sensitive data redaction.","intents":["I want to trace MCP requests through my server and see execution timing for each tool","I need to collect metrics on tool usage, error rates, and latency for monitoring","I want to debug production issues by reviewing structured logs with full request context"],"best_for":["production MCP deployments requiring debugging and monitoring","teams using centralized logging platforms (Datadog, New Relic, etc.)","developers building observability-first MCP architectures"],"limitations":["Structured logging adds ~5-10ms overhead per request","Sensitive data redaction requires explicit configuration — defaults to logging all fields","OpenTelemetry integration requires external collector setup"],"requires":["observability platform or log aggregation service (optional but recommended)","OpenTelemetry SDK (if using OTEL export)","configuration of log levels and sampling rates"],"input_types":["MCP requests and responses","execution context","error information"],"output_types":["structured logs (JSON)","traces (OpenTelemetry format)","metrics (Prometheus format)"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-mcp-usecli__cap_8","uri":"capability://code.generation.editing.code.mode.code.execution.support","name":"code mode (code execution) support","description":"Configures MCP servers to support Code Mode, enabling ChatGPT to execute code snippets in a sandboxed environment managed by the MCP server. Handles code execution requests, output capture, and error handling. Manages sandbox lifecycle and resource limits.","intents":["I want to enable ChatGPT to execute Python/JavaScript code against my MCP server","I need to provide a sandboxed code execution environment for ChatGPT Code Mode","I want to capture and return code execution output to ChatGPT"],"best_for":["MCP servers providing computational or data analysis capabilities","teams building ChatGPT integrations with code execution","data science and analytics tool providers"],"limitations":["Sandbox implementation is custom — no built-in security guarantees","Code execution timeout and resource limits must be configured manually","No built-in support for persistent state between code executions"],"requires":["ChatGPT Code Mode support (requires specific ChatGPT App configuration)","code execution runtime (Python, Node.js, etc.)","sandbox or containerization solution (Docker, etc.)"],"input_types":["code snippets (Python, JavaScript, etc.)","execution parameters"],"output_types":["execution results","stdout/stderr output","error messages"],"categories":["code-generation-editing","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-mcp-usecli__cap_9","uri":"capability://code.generation.editing.react.component.ui.rendering.for.mcp.tools","name":"react component ui rendering for mcp tools","description":"Enables MCP tools to return React components as responses, which are rendered in ChatGPT's UI. Handles component serialization, prop passing, and event handling. Manages the bridge between MCP's JSON response format and React's component model. Supports interactive components with state management.","intents":["I want my MCP tool to return a rich interactive UI component instead of plain text","I need to render data visualizations or forms in ChatGPT using React components","I want to handle user interactions (clicks, form submissions) in my MCP tool responses"],"best_for":["MCP tools providing data visualization or interactive interfaces","teams building ChatGPT Apps with rich UI requirements","developers familiar with React component development"],"limitations":["Component serialization adds overhead — complex components may have performance impact","Limited to React components — no Vue, Svelte, or other frameworks","Event handling requires round-trip to MCP server — no client-side-only interactions"],"requires":["React 18+","MCP client with React component rendering support","ChatGPT App with UI component support"],"input_types":["React component definitions","component props (JSON-serializable)"],"output_types":["rendered React components","component event handlers"],"categories":["code-generation-editing","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":32,"verified":false,"data_access_risk":"high","permissions":["Node.js 18+","npm or yarn package manager","Basic familiarity with MCP protocol concepts","TypeScript 4.5+ (for type checking)","esbuild installed as dependency","cloud provider account and credentials","provider-specific CLI tools (AWS CLI, gcloud, etc.)","understanding of provider-specific deployment models","OpenAI API key with ChatGPT Apps access","OAuth provider credentials (client ID, secret)"],"failure_modes":["Limited to TypeScript/JavaScript — no Python or Go templates","Assumes esbuild as the bundler — no webpack or Vite alternatives","Generated projects require manual OAuth configuration if needed","esbuild-only — no support for webpack or Rollup configurations","Tree-shaking effectiveness depends on ESM module structure in dependencies","No built-in code splitting for large monorepo MCP server collections","Provider-specific optimizations require manual tuning per platform","Serverless deployments have cold start latency — not suitable for latency-critical tools","Credential management is provider-specific — no unified secret handling","ChatGPT App deployment requires OpenAI organization approval","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.47,"ecosystem":0.5000000000000001,"match_graph":0.25,"freshness":0.6,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.28,"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":"2026-05-03T14:23:52.694Z","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-mcp-usecli","compare_url":"https://unfragile.ai/compare?artifact=npm-mcp-usecli"}},"signature":"TYAm7qVYrMZ16neLwIM56Hn2WMYDPzsG8Zd4FV2xrZK69JA1zdiOmB/a2mYDR9TyLdFvgFoQcUFV0e1XNr3wAw==","signedAt":"2026-06-19T20:29:44.899Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/npm-mcp-usecli","artifact":"https://unfragile.ai/npm-mcp-usecli","verify":"https://unfragile.ai/api/v1/verify?slug=npm-mcp-usecli","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"}}