{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"awesome-supadata","slug":"supadata","name":"Supadata","type":"mcp","url":"https://github.com/supadata-ai/mcp","page_url":"https://unfragile.ai/supadata","categories":["mcp-servers"],"tags":[],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"awesome-supadata__cap_0","uri":"capability://data.processing.analysis.video.transcript.extraction.with.platform.specific.parsing","name":"video transcript extraction with platform-specific parsing","description":"Extracts full transcripts from YouTube, TikTok, Instagram, and Twitter videos by integrating with the Supadata API, which handles platform-specific authentication, caption retrieval, and text normalization. The MCP server wraps this via the supadata_transcript tool, routing requests through either stdio (local) or Cloudflare Workers (edge) transport layers, with built-in exponential backoff retry logic for rate-limited responses (429 errors).","intents":["I need to extract the full transcript from a YouTube video to feed into my LLM for analysis","I want to get captions from a TikTok video without manually downloading them","I'm building an agent that needs to understand video content as text for semantic search"],"best_for":["AI agents and LLM applications that need to process video content as context","Developers building research tools that aggregate multi-platform video data","Teams automating content analysis workflows across YouTube, TikTok, and social media"],"limitations":["Requires valid Supadata API key with active quota — no free tier mentioned","Transcript availability depends on platform (some videos may lack captions)","Asynchronous extraction for long videos requires polling via supadata_check_*_status tools","No built-in caching — repeated requests for same video incur API costs"],"requires":["Node.js 18+","SUPADATA_API_KEY environment variable","MCP-compatible client (Claude Desktop, Cursor, VS Code)","Valid video URL from supported platform (YouTube, TikTok, Instagram, Twitter)"],"input_types":["video URL (string)","platform identifier (implicit from URL)"],"output_types":["plain text transcript","structured JSON with timestamps (if available)"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-supadata__cap_1","uri":"capability://data.processing.analysis.video.metadata.and.structured.extraction.with.ai.enrichment","name":"video metadata and structured extraction with ai enrichment","description":"Retrieves metadata (title, duration, channel info, upload date) and performs AI-powered structured data extraction from video content via supadata_metadata and supadata_extract tools. The extraction uses the Supadata API's LLM-based parsing to convert unstructured video content into schema-compliant JSON, with configurable output schemas passed as tool parameters.","intents":["I need to extract structured data (speaker names, key topics, timestamps) from a video","I want to get video metadata (duration, channel, publish date) to enrich my database","I'm building a content catalog and need AI to extract entities (products mentioned, sentiment) from videos"],"best_for":["Content management systems that need to index and catalog video metadata","LLM agents performing multi-step reasoning that requires structured video insights","Data pipelines extracting specific entities or facts from video content"],"limitations":["Structured extraction quality depends on schema clarity and video content complexity","No streaming output — full extraction must complete before returning results","Schema validation errors are not caught until API response — no client-side schema validation","Extraction latency scales with video length (long videos may timeout)"],"requires":["Node.js 18+","SUPADATA_API_KEY with extraction quota","MCP-compatible client","Optional: JSON schema for structured extraction (supadata_extract)"],"input_types":["video URL (string)","JSON schema (optional, for supadata_extract)","extraction parameters (optional)"],"output_types":["JSON metadata object (title, duration, channel, upload_date)","JSON structured data matching provided schema"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-supadata__cap_10","uri":"capability://automation.workflow.github.actions.ci.cd.pipeline.with.automated.testing.and.deployment","name":"github actions ci/cd pipeline with automated testing and deployment","description":"Includes GitHub Actions workflows that automate testing, building, and deployment of the Supadata MCP server. The workflows run the test suite (src/index.test.ts), build Docker images, and deploy to container registries or cloud platforms. This enables continuous integration and deployment without manual intervention.","intents":["I want to automatically test my Supadata MCP server on every commit","I need to build and push Docker images to a registry on each release","I'm setting up CI/CD for my agent platform that includes Supadata tools"],"best_for":["Teams using GitHub for version control and CI/CD","DevOps engineers automating deployment pipelines","Organizations standardizing on GitHub Actions for infrastructure automation"],"limitations":["GitHub Actions workflows are specific to GitHub — not portable to other CI/CD platforms","Workflow configuration requires understanding of GitHub Actions syntax","Secrets (API keys, registry credentials) must be configured in GitHub repository settings","Workflow execution time depends on test suite and build complexity"],"requires":["GitHub repository with Actions enabled","GitHub Actions secrets configured (SUPADATA_API_KEY, registry credentials, etc.)","Workflow files in .github/workflows/ directory"],"input_types":["Git commits and pull requests (trigger events)","GitHub Actions secrets (credentials)"],"output_types":["test results (pass/fail)","Docker images (pushed to registry)","deployment status (success/failure)"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-supadata__cap_11","uri":"capability://tool.use.integration.smithery.mcp.registry.integration.for.tool.discovery","name":"smithery mcp registry integration for tool discovery","description":"Integrates with the Smithery MCP registry, allowing the Supadata MCP server to be discovered and installed via the Smithery package manager. This enables developers to install Supadata tools via a single command without manually cloning the repository or managing dependencies.","intents":["I want to install Supadata tools via Smithery without cloning the repository","I need to discover available MCP servers including Supadata in a central registry","I'm building an agent platform and want to install Supadata tools from a package manager"],"best_for":["Developers using Smithery as their MCP package manager","Teams standardizing on Smithery for MCP server discovery and installation","Organizations building agent platforms that integrate multiple MCP servers"],"limitations":["Requires Smithery to be installed and configured","Smithery registry availability depends on external service uptime","Package updates may lag behind GitHub releases","No built-in version pinning — Smithery may install different versions than expected"],"requires":["Smithery package manager installed","Smithery registry access (internet connection)","Supadata MCP server listed in Smithery registry"],"input_types":["Smithery install command (CLI input)"],"output_types":["installed MCP server (local installation)"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-supadata__cap_2","uri":"capability://data.processing.analysis.single.page.web.scraping.with.markdown.normalization","name":"single-page web scraping with markdown normalization","description":"Scrapes a single web page and returns content as normalized Markdown via the supadata_scrape tool. The tool handles HTML parsing, content extraction, and Markdown conversion server-side, returning clean, LLM-friendly text without requiring client-side DOM manipulation or HTML parsing libraries. Integrates with the Supadata API's web scraping engine, which abstracts away JavaScript rendering and dynamic content challenges.","intents":["I need to extract the main content from a web page and feed it to my LLM","I want to scrape a single URL without dealing with HTML parsing or JavaScript rendering","I'm building an agent that needs to read web pages as context for decision-making"],"best_for":["LLM agents that need to read web content as context without client-side rendering","Developers building research or data collection tools that need clean text from web pages","Teams automating content ingestion from websites into knowledge bases"],"limitations":["Single-page only — does not follow links or crawl multiple pages (use supadata_crawl for that)","Markdown output may lose some formatting or structural nuance from original HTML","No JavaScript execution control — dynamic content rendering is handled by Supadata API, not configurable","Rate limiting applies per API key — high-volume scraping requires quota management"],"requires":["Node.js 18+","SUPADATA_API_KEY","MCP-compatible client","Valid HTTP(S) URL"],"input_types":["URL (string)","optional: headers or user-agent overrides"],"output_types":["Markdown text","plain text"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-supadata__cap_3","uri":"capability://search.retrieval.site.wide.url.discovery.and.mapping","name":"site-wide url discovery and mapping","description":"Discovers all URLs on a website via the supadata_map tool, which crawls the site's structure and returns a list of discoverable URLs. This tool is designed for reconnaissance before batch crawling, allowing developers to understand site topology without fetching full page content. Uses the Supadata API's crawler to follow internal links and build a URL map, respecting robots.txt and site structure.","intents":["I need to discover all pages on a website before deciding which ones to crawl","I want to understand the structure of a site to plan a targeted scraping strategy","I'm building a crawler that needs to know all available URLs before fetching content"],"best_for":["Developers planning large-scale web scraping operations who need to scope the task","Teams building site-aware agents that need to understand information architecture","Research tools that need to map competitor or reference websites"],"limitations":["Does not return page content — only URLs (use supadata_scrape or supadata_crawl for content)","May not discover dynamically-generated URLs (JavaScript-rendered links)","Respects robots.txt, which may limit discovery on some sites","Large sites may return thousands of URLs — no built-in pagination or filtering"],"requires":["Node.js 18+","SUPADATA_API_KEY","MCP-compatible client","Valid domain URL"],"input_types":["domain URL (string)","optional: depth limit, URL filters"],"output_types":["JSON array of discovered URLs","plain text list of URLs"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-supadata__cap_4","uri":"capability://automation.workflow.asynchronous.batch.web.crawling.with.job.polling","name":"asynchronous batch web crawling with job polling","description":"Crawls multiple URLs asynchronously via the supadata_crawl tool, which queues a batch job and returns a job ID. Developers then poll the job status using supadata_check_*_status tools with exponential backoff retry logic. The server manages the async job lifecycle, storing results server-side and returning them when complete. This pattern decouples request submission from result retrieval, enabling high-volume crawling without blocking.","intents":["I need to crawl 100+ URLs from a website and get their content as Markdown","I want to submit a large scraping job and check its status without blocking my agent","I'm building a data pipeline that needs to fetch content from multiple pages in parallel"],"best_for":["Agents and workflows that need to crawl many URLs without blocking execution","Data pipelines performing large-scale content ingestion from websites","Teams building research tools that aggregate content from multiple pages"],"limitations":["Asynchronous pattern requires polling — no webhooks or event-driven completion notifications","Job results are stored server-side temporarily — developers must retrieve them within a time window","No built-in result streaming — full crawl must complete before results are available","Polling adds latency — developers must implement retry logic and backoff strategies","Rate limiting applies across all concurrent jobs — high concurrency may hit quota limits"],"requires":["Node.js 18+","SUPADATA_API_KEY with batch crawling quota","MCP-compatible client","Job polling loop (manual or via agent framework)"],"input_types":["array of URLs (JSON array)","optional: crawl depth, content filters, output format"],"output_types":["job ID (string, returned immediately)","crawl results (JSON array of {url, content, metadata}, returned on polling)"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-supadata__cap_5","uri":"capability://automation.workflow.job.status.polling.with.exponential.backoff.retry","name":"job status polling with exponential backoff retry","description":"Provides supadata_check_*_status tools that poll the status of asynchronous jobs (transcripts, crawls, extractions) with configurable exponential backoff retry logic. The server implements SUPADATA_RETRY_MAX_ATTEMPTS and SUPADATA_RETRY_INITIAL_DELAY configuration variables to control retry behavior, automatically handling transient failures and rate limits (429 errors) without requiring client-side retry logic.","intents":["I need to check if my async crawl job has completed","I want to poll a transcript extraction job with automatic retry on failure","I'm building an agent that needs robust polling with backoff to handle rate limits"],"best_for":["Agents and workflows using async Supadata tools that need reliable polling","Developers building resilient data pipelines that handle transient API failures","Teams automating content extraction with built-in retry logic"],"limitations":["Polling-based pattern adds latency — no push notifications or webhooks","Retry configuration is global (SUPADATA_RETRY_MAX_ATTEMPTS) — no per-job tuning","Exponential backoff may delay result retrieval for time-sensitive operations","No built-in timeout — developers must implement their own max polling duration"],"requires":["Node.js 18+","SUPADATA_API_KEY","MCP-compatible client","Job ID from a prior async operation (supadata_crawl, supadata_transcript, etc.)","Optional: SUPADATA_RETRY_MAX_ATTEMPTS and SUPADATA_RETRY_INITIAL_DELAY env vars"],"input_types":["job ID (string)","optional: retry configuration overrides"],"output_types":["job status (pending, completed, failed)","results (if completed)","error details (if failed)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-supadata__cap_6","uri":"capability://tool.use.integration.mcp.protocol.transport.abstraction.with.dual.deployment.modes","name":"mcp protocol transport abstraction with dual deployment modes","description":"Provides a unified MCP tool interface that works across two transport layers: stdio (local/CLI via src/index.ts) and Cloudflare Workers (edge/serverless via src/worker.ts). The MCP Tool Engine (src/mcp.ts) defines all tools once, and the transport layer abstracts away the underlying communication protocol. Developers can run the same tool definitions locally via npx or deploy to edge infrastructure without code changes.","intents":["I want to run Supadata tools locally in my IDE (Claude Desktop, Cursor, VS Code)","I need to deploy Supadata tools to a serverless edge environment (Cloudflare Workers)","I'm building an agent that should work in both local and cloud environments"],"best_for":["Developers using MCP-compatible IDEs (Claude Desktop, Cursor, VS Code) who want local tool access","Teams deploying agents to serverless/edge infrastructure (Cloudflare Workers)","Organizations needing flexibility to run tools locally or in the cloud without code duplication"],"limitations":["Stdio transport requires local Node.js process — not suitable for web browsers or non-Node environments","Cloudflare Workers deployment requires Wrangler CLI and Cloudflare account setup","OAuth 2.0 flow is implemented for Workers but requires additional configuration (wrangler.toml)","No built-in load balancing or auto-scaling — Cloudflare Workers handles that separately"],"requires":["Node.js 18+ (for stdio)","Cloudflare account and Wrangler CLI (for Workers deployment)","SUPADATA_API_KEY environment variable","MCP-compatible client (Claude Desktop, Cursor, VS Code) for stdio mode"],"input_types":["MCP tool requests (JSON-RPC format)"],"output_types":["MCP tool responses (JSON-RPC format)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-supadata__cap_7","uri":"capability://tool.use.integration.oauth.2.0.authentication.for.edge.deployment","name":"oauth 2.0 authentication for edge deployment","description":"Implements OAuth 2.0 flow for Cloudflare Workers deployment via src/auth-handler.ts and wrangler.toml configuration. Handles user authentication, token exchange, and credential storage for edge-deployed agents. The server manages the OAuth handshake and securely stores credentials in Cloudflare KV storage, enabling multi-user deployments without exposing API keys to clients.","intents":["I need to deploy Supadata tools to Cloudflare Workers with multi-user support","I want to authenticate users via OAuth without exposing API keys","I'm building a SaaS application that needs to securely manage user credentials for Supadata API access"],"best_for":["Teams deploying agents to Cloudflare Workers with multiple end users","SaaS applications that need to manage user credentials securely","Organizations requiring OAuth-based authentication for edge-deployed tools"],"limitations":["OAuth configuration requires Cloudflare account and wrangler.toml setup","Credentials are stored in Cloudflare KV — subject to KV storage limits and pricing","No built-in token refresh logic — tokens may expire and require re-authentication","OAuth flow requires a callback URL — not suitable for CLI-only deployments"],"requires":["Cloudflare account","Wrangler CLI installed and configured","OAuth provider configuration (client ID, client secret)","Cloudflare KV namespace for credential storage","wrangler.toml with OAuth settings"],"input_types":["OAuth authorization code (from provider)","user credentials (managed by OAuth flow)"],"output_types":["access token (stored in Cloudflare KV)","user identity (from OAuth provider)"],"categories":["tool-use-integration","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-supadata__cap_8","uri":"capability://automation.workflow.environment.based.configuration.with.retry.tuning","name":"environment-based configuration with retry tuning","description":"Provides centralized configuration via environment variables (SUPADATA_API_KEY, SUPADATA_RETRY_MAX_ATTEMPTS, SUPADATA_RETRY_INITIAL_DELAY) that control API authentication, retry behavior, and backoff strategy. The server loads configuration via dotenv for local deployments and environment variables for cloud deployments, allowing operators to tune retry behavior without code changes.","intents":["I need to configure retry behavior for my Supadata tools","I want to set different API keys for different environments (dev, staging, prod)","I'm tuning my agent's resilience to handle rate limits better"],"best_for":["DevOps teams managing Supadata deployments across environments","Developers tuning agent resilience and retry behavior","Teams deploying to multiple environments with different API quotas"],"limitations":["Configuration is global — no per-tool or per-request overrides","Retry configuration changes require server restart","No built-in configuration validation — invalid values may cause silent failures","dotenv only works for local deployments — cloud deployments require environment variable setup"],"requires":["Node.js 18+",".env file (for local deployments) or environment variables (for cloud)","SUPADATA_API_KEY (required)","SUPADATA_RETRY_MAX_ATTEMPTS and SUPADATA_RETRY_INITIAL_DELAY (optional)"],"input_types":["environment variables (string values)"],"output_types":["configuration object (used internally by server)"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-supadata__cap_9","uri":"capability://automation.workflow.docker.containerization.with.multi.stage.build","name":"docker containerization with multi-stage build","description":"Provides a multi-stage Dockerfile (node:22-alpine base) that builds the Supadata MCP server in a container, enabling deployment to Docker-compatible environments (Kubernetes, Docker Compose, container registries). The build process compiles TypeScript, installs dependencies, and creates a minimal runtime image optimized for production deployment.","intents":["I need to deploy Supadata tools in a Kubernetes cluster","I want to run the MCP server in a Docker container for consistency across environments","I'm building a containerized agent platform that includes Supadata tools"],"best_for":["DevOps teams deploying agents to Kubernetes or container orchestration platforms","Organizations standardizing on Docker for infrastructure consistency","Teams building containerized agent platforms with Supadata integration"],"limitations":["Docker deployment requires Docker or container runtime installed","Multi-stage build adds complexity — requires understanding of Dockerfile syntax","Container image size depends on Node.js base image (node:22-alpine is ~150MB)","No built-in health checks or readiness probes — must be configured separately"],"requires":["Docker or compatible container runtime","Dockerfile (provided in repo)","SUPADATA_API_KEY (passed as environment variable to container)"],"input_types":["Dockerfile (build input)","environment variables (runtime input)"],"output_types":["Docker image (build output)","running container (runtime output)"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":32,"verified":false,"data_access_risk":"high","permissions":["Node.js 18+","SUPADATA_API_KEY environment variable","MCP-compatible client (Claude Desktop, Cursor, VS Code)","Valid video URL from supported platform (YouTube, TikTok, Instagram, Twitter)","SUPADATA_API_KEY with extraction quota","MCP-compatible client","Optional: JSON schema for structured extraction (supadata_extract)","GitHub repository with Actions enabled","GitHub Actions secrets configured (SUPADATA_API_KEY, registry credentials, etc.)","Workflow files in .github/workflows/ directory"],"failure_modes":["Requires valid Supadata API key with active quota — no free tier mentioned","Transcript availability depends on platform (some videos may lack captions)","Asynchronous extraction for long videos requires polling via supadata_check_*_status tools","No built-in caching — repeated requests for same video incur API costs","Structured extraction quality depends on schema clarity and video content complexity","No streaming output — full extraction must complete before returning results","Schema validation errors are not caught until API response — no client-side schema validation","Extraction latency scales with video length (long videos may timeout)","GitHub Actions workflows are specific to GitHub — not portable to other CI/CD platforms","Workflow configuration requires understanding of GitHub Actions syntax","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.49,"ecosystem":0.39999999999999997,"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":"2026-06-17T09:51:04.049Z","last_scraped_at":"2026-05-03T14:00:15.503Z","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=supadata","compare_url":"https://unfragile.ai/compare?artifact=supadata"}},"signature":"hYdyYTb2NvxrgoDGWPwOplXZDwmdj6U4DlDgAGcA3QkTEKF+N7Vg0MLoumB/x0/+0q4Z71JlitQcxym9ry8iAA==","signedAt":"2026-06-21T00:50:15.454Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/supadata","artifact":"https://unfragile.ai/supadata","verify":"https://unfragile.ai/api/v1/verify?slug=supadata","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"}}