{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"github-activepieces--activepieces","slug":"activepieces--activepieces","name":"activepieces","type":"platform","url":"https://www.activepieces.com","page_url":"https://unfragile.ai/activepieces--activepieces","categories":["automation"],"tags":["ai-agent","ai-agent-tools","ai-agents","ai-agents-framework","mcp","mcp-server","mcp-tools","mcps","n8n-alternative","no-code-automation","workflow","workflow-automation","workflows"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"github-activepieces--activepieces__cap_0","uri":"capability://automation.workflow.visual.flow.builder.with.drag.and.drop.workflow.composition","name":"visual flow builder with drag-and-drop workflow composition","description":"Provides a React-based frontend UI that enables users to visually compose automation workflows by dragging action/trigger pieces onto a canvas and connecting them with data flow edges. The builder maintains a JSON-serialized flow definition that maps to the backend execution engine, with real-time validation of piece inputs/outputs and visual feedback for connection compatibility. State management via a centralized store tracks flow structure, piece configurations, and variable bindings.","intents":["I want to build a multi-step automation without writing code","I need to visually see how data flows between different API calls and actions","I want to test individual steps in my workflow before running the full automation"],"best_for":["Non-technical business users automating repetitive tasks","Teams migrating from Zapier/Make who want visual workflow design","Developers prototyping integrations quickly without boilerplate"],"limitations":["Complex conditional logic requires switching to code mode or using router pieces","Large workflows (100+ steps) may experience UI lag due to canvas rendering overhead","No collaborative real-time editing — single user per flow at a time"],"requires":["Modern browser with ES2020+ support (Chrome 90+, Firefox 88+, Safari 14+)","Activepieces server running with frontend assets served","Active user session with flow edit permissions"],"input_types":["flow definition JSON","piece configuration objects"],"output_types":["flow definition JSON","executable flow graph"],"categories":["automation-workflow","ui-builder"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-activepieces--activepieces__cap_1","uri":"capability://tool.use.integration.modular.pieces.framework.with.400.pre.built.integrations","name":"modular pieces framework with 400+ pre-built integrations","description":"Implements a plugin architecture where each integration (Discord, Google Drive, Claude, etc.) is a self-contained 'piece' package exporting actions and triggers via a standardized TypeScript interface. Pieces declare their inputs/outputs as JSON schemas, authentication requirements, and execution logic. The framework loads pieces dynamically at runtime via a piece-loader service that resolves dependencies, validates schemas, and injects authenticated connections from the connection management service.","intents":["I want to connect my workflow to 400+ SaaS platforms without custom code","I need to create a custom integration for my internal API","I want to reuse the same authentication across multiple pieces in a workflow"],"best_for":["Teams building integrations across diverse SaaS ecosystems","Enterprise users needing custom pieces for proprietary APIs","Open-source contributors extending the platform with new integrations"],"limitations":["Pieces are TypeScript-only — no Python, Go, or other language SDKs for custom pieces","Each piece is independently versioned; breaking changes in one piece don't auto-propagate to dependent flows","No built-in rate limiting per piece — relies on downstream API rate limits"],"requires":["TypeScript 4.9+","Node.js 18+ for piece development","Activepieces piece framework package (@activepieces/pieces-framework)","API credentials for the target service"],"input_types":["JSON schema definitions","authentication tokens","user input parameters"],"output_types":["action results (JSON)","trigger events (JSON)","error objects"],"categories":["tool-use-integration","plugin-architecture"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-activepieces--activepieces__cap_10","uri":"capability://automation.workflow.error.handling.and.retry.logic.with.exponential.backoff","name":"error handling and retry logic with exponential backoff","description":"Provides configurable error handling at the piece and flow level. Pieces can define error handlers that catch failures and trigger alternative actions. The execution engine supports automatic retries with exponential backoff (e.g., 1s, 2s, 4s, 8s) for transient failures. Retry logic is configurable per piece (max retries, backoff strategy). Failed steps can trigger error handlers that log, notify, or attempt recovery. Errors are tracked in the database for debugging and monitoring.","intents":["I want my workflow to automatically retry failed API calls due to temporary network issues","I need to handle errors gracefully without stopping the entire workflow","I want to log errors and send notifications when a workflow fails"],"best_for":["Workflows integrating with unreliable APIs or networks","Mission-critical automations requiring high reliability","Teams needing detailed error logs for debugging"],"limitations":["Retry logic is per-piece — no global retry strategy across the flow","Exponential backoff is fixed (1s, 2s, 4s, 8s) — not customizable","Max retries are capped at 10 to prevent infinite loops","Errors are not automatically escalated to external monitoring systems"],"requires":["Piece configuration with retry settings","Error handler pieces (log, notify, etc.) for handling failures","Database for storing error logs"],"input_types":["error objects","retry configuration"],"output_types":["retry attempts","error logs","error handler results"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-activepieces--activepieces__cap_11","uri":"capability://automation.workflow.real.time.execution.monitoring.and.debugging.ui","name":"real-time execution monitoring and debugging ui","description":"Provides a web-based UI for monitoring flow executions in real-time, showing step-by-step progress, intermediate outputs, and error details. The UI connects via WebSocket to the server's ProgressService, receiving live updates as steps execute. Users can inspect the output of each step, view variable values, and trace data flow through the workflow. Failed executions show detailed error messages and stack traces. The UI supports filtering and searching execution history.","intents":["I want to see what's happening in my workflow as it executes","I need to debug a failed workflow by inspecting intermediate step outputs","I want to search and filter my execution history to find specific runs"],"best_for":["Developers debugging complex workflows","Teams troubleshooting integration issues","Operators monitoring production workflows"],"limitations":["Real-time updates are limited to active WebSocket connections — historical data requires database queries","Large execution logs (100+ steps) may cause UI lag","No built-in log aggregation — logs are stored in the database only","WebSocket connections are not persisted across server restarts"],"requires":["Modern browser with WebSocket support","Activepieces server with WebSocket endpoint","Database for storing execution history","User access to the flow execution details"],"input_types":["execution progress updates","step outputs","error logs"],"output_types":["UI rendering of execution state","downloadable execution logs"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-activepieces--activepieces__cap_12","uri":"capability://tool.use.integration.mcp.model.context.protocol.server.integration.for.ai.agent.tool.use","name":"mcp (model context protocol) server integration for ai agent tool use","description":"Implements Activepieces as an MCP server, exposing flows and pieces as tools that AI agents (Claude, GPT, etc.) can invoke. Each piece is registered as an MCP tool with its JSON schema, allowing agents to discover available integrations and call them with natural language. The MCP server translates agent requests into flow executions, returning results back to the agent. This enables AI agents to autonomously execute multi-step workflows without explicit user orchestration.","intents":["I want my AI agent to autonomously execute workflows by calling Activepieces as an MCP server","I need to expose my integrations to Claude or GPT as discoverable tools","I want to enable AI agents to chain multiple API calls together without manual orchestration"],"best_for":["Teams building AI agents that need to execute multi-step automations","Developers integrating Activepieces with Claude, GPT, or other LLMs","Enterprises enabling AI agents to autonomously manage integrations"],"limitations":["MCP server requires explicit tool registration — not all pieces are automatically exposed","Agent execution is asynchronous — no real-time feedback to the agent during execution","MCP tools are limited to simple input/output — complex state management is not supported","No built-in rate limiting per agent — relies on quota system"],"requires":["Activepieces server with MCP server enabled","AI agent platform supporting MCP (Claude, GPT with MCP plugin, etc.)","Tool registration for each piece to be exposed to agents","API key for agent authentication"],"input_types":["MCP tool calls from AI agents","tool parameters (JSON)"],"output_types":["tool results (JSON)","execution status","error messages"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-activepieces--activepieces__cap_13","uri":"capability://text.generation.language.internationalization.i18n.with.multi.language.ui.support","name":"internationalization (i18n) with multi-language ui support","description":"Provides a translation system for the Activepieces UI, supporting multiple languages (English, Spanish, French, German, etc.). The frontend uses i18n libraries to load language-specific strings from JSON files and render the UI in the user's preferred language. Language selection is stored in user preferences and applied globally. The system supports right-to-left (RTL) languages and locale-specific formatting (dates, numbers, currency).","intents":["I want to use Activepieces in my native language","I need to deploy Activepieces to international teams with different language preferences","I want to support RTL languages like Arabic and Hebrew"],"best_for":["Global teams using Activepieces across multiple regions","SaaS providers offering Activepieces to international customers","Enterprises deploying Activepieces in non-English-speaking countries"],"limitations":["Piece documentation and error messages are not automatically translated","Adding new languages requires manual translation of all UI strings","RTL support is limited to UI layout — flow definitions are still LTR","No built-in translation management tool — translations are stored in JSON files"],"requires":["i18n library configured in the frontend (e.g., react-i18next)","Translation files for each supported language","User preference storage for language selection"],"input_types":["language code (e.g., 'en', 'es', 'fr')","translation strings"],"output_types":["localized UI strings","formatted dates/numbers/currency"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-activepieces--activepieces__cap_2","uri":"capability://automation.workflow.flow.execution.engine.with.step.by.step.execution.and.state.management","name":"flow execution engine with step-by-step execution and state management","description":"A TypeScript-based execution runtime (packages/engine) that interprets flow definitions as directed acyclic graphs, executing pieces sequentially or in parallel based on flow topology. The engine maintains execution context (FlowExecutionContext) tracking variables, step outputs, and execution state. It handles piece execution via PieceExecutor, code execution via CodeExecutor with sandboxing, loops via LoopExecutor, and conditional routing via RouterExecutor. Progress is tracked in real-time via a ProgressService and persisted to the database for resumability.","intents":["I want my workflow to execute reliably with automatic retry on transient failures","I need to pause a long-running workflow and resume it later without losing state","I want to debug a failed workflow step by step with access to intermediate outputs"],"best_for":["Teams running mission-critical automations requiring high reliability","Workflows with long execution times (hours/days) that need pause/resume","Developers debugging complex multi-step integrations"],"limitations":["Execution is single-threaded per flow instance — parallel steps are simulated, not true concurrency","State persistence adds ~100-200ms per step due to database writes","Code execution sandbox has ~5s timeout per code block to prevent runaway scripts","No distributed execution — all steps run on a single worker node"],"requires":["Node.js 18+","Database connection (PostgreSQL, SQLite, or MySQL) for state persistence","Worker process with sufficient memory (512MB+ recommended)","Piece packages installed and registered in the piece loader"],"input_types":["flow definition JSON","trigger event data","execution context"],"output_types":["step outputs (JSON)","flow completion status","error logs"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-activepieces--activepieces__cap_3","uri":"capability://automation.workflow.webhook.triggered.flow.activation.with.payload.validation","name":"webhook-triggered flow activation with payload validation","description":"Exposes HTTP endpoints that accept incoming webhooks and map them to flow triggers. The webhook handler validates incoming payloads against the trigger's JSON schema, extracts relevant data, and enqueues a flow execution job with the webhook payload as the trigger input. Supports multiple webhook URLs per flow for different trigger types. Webhooks are authenticated via API keys or OAuth tokens depending on the flow's security configuration.","intents":["I want to trigger a workflow when an external service sends a webhook (GitHub push, Stripe charge, etc.)","I need to validate incoming webhook payloads before processing them","I want to expose a unique webhook URL for each flow without managing custom code"],"best_for":["Teams integrating with webhook-enabled SaaS platforms (GitHub, Stripe, Slack)","Event-driven automation use cases (CI/CD pipelines, payment processing)","Users avoiding custom webhook servers for simple integrations"],"limitations":["Webhook payloads are limited to 10MB per request","No built-in webhook retry logic — if flow execution fails, the webhook is not retried","Webhook URLs are long-lived and cannot be rotated without updating the external service","No request signing verification — relies on API key authentication only"],"requires":["Activepieces server with public HTTP endpoint (not behind strict firewall)","Flow with a webhook trigger piece configured","API key for webhook authentication (if not using OAuth)","External service capable of sending HTTP POST requests"],"input_types":["HTTP POST body (JSON or form-encoded)","HTTP headers","query parameters"],"output_types":["flow execution job ID","HTTP 200 response","validation error (HTTP 400)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-activepieces--activepieces__cap_4","uri":"capability://automation.workflow.queue.based.worker.architecture.for.distributed.flow.execution","name":"queue-based worker architecture for distributed flow execution","description":"Implements a job queue (using Bull or similar) where flow executions are enqueued as jobs and processed by worker processes. The server enqueues execution jobs; workers dequeue and execute them using the flow execution engine. This decouples flow submission from execution, enabling horizontal scaling by adding more workers. Workers report progress back to the server via the ProgressService, which updates the database and broadcasts to connected clients via WebSockets.","intents":["I want to scale my automation platform to handle thousands of concurrent workflows","I need workers to execute flows in isolation without blocking the API server","I want to monitor execution progress in real-time across multiple worker processes"],"best_for":["Enterprise deployments with high workflow volume (100+ concurrent executions)","Teams requiring fault isolation between flow executions","Operators needing to scale workers independently from the API server"],"limitations":["Queue adds ~500ms-2s latency between flow submission and execution start","Worker crashes lose in-flight jobs unless persistence is configured","No built-in job prioritization — all jobs are processed FIFO","Requires Redis or similar queue backend (adds operational complexity)"],"requires":["Redis 6.0+ or compatible queue backend","Multiple Node.js processes (one server, N workers)","Database for job persistence and progress tracking","Network connectivity between server and workers"],"input_types":["flow execution job objects","trigger event data"],"output_types":["execution progress updates","completion status","error logs"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-activepieces--activepieces__cap_5","uri":"capability://tool.use.integration.authentication.and.connection.management.with.oauth.and.api.key.support","name":"authentication and connection management with oauth and api key support","description":"Provides a centralized connection management system where users authenticate once to a service (via OAuth, API key, or basic auth) and the credentials are stored encrypted in the database. Pieces reference connections by ID, and the ConnectionService injects authenticated clients into piece execution. Supports multiple authentication methods per service (e.g., OAuth for user-scoped access, API key for service accounts). Credentials are encrypted at rest using the platform's encryption key.","intents":["I want to authenticate to an API once and reuse the credentials across multiple workflows","I need to securely store API keys without exposing them in flow definitions","I want to support both OAuth and API key authentication for the same service"],"best_for":["Multi-user platforms where credentials must be isolated per user","Enterprise deployments requiring credential encryption and audit trails","Teams integrating with OAuth-enabled services (Google, GitHub, Slack)"],"limitations":["OAuth tokens are not automatically refreshed — requires manual re-authentication when expired","Credentials are encrypted with a single platform key — no per-user key derivation","No credential rotation mechanism — users must manually update credentials if compromised","API key authentication is plaintext in the database until encryption is enabled"],"requires":["Database for storing encrypted credentials","Encryption key configured in environment (AP_ENCRYPTION_KEY)","OAuth client credentials for services using OAuth","HTTPS for OAuth redirect URIs (required by most OAuth providers)"],"input_types":["OAuth authorization codes","API keys","username/password pairs"],"output_types":["connection objects with encrypted credentials","authenticated HTTP clients"],"categories":["tool-use-integration","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-activepieces--activepieces__cap_6","uri":"capability://code.generation.editing.code.execution.sandbox.for.custom.javascript.logic.in.workflows","name":"code execution sandbox for custom javascript logic in workflows","description":"Allows users to write custom JavaScript code blocks within workflows that execute in an isolated sandbox (using vm2 or similar). The sandbox has access to the flow execution context (variables, step outputs) but is restricted from accessing the file system, network, or other sensitive resources. Code blocks are executed with a 5-second timeout and can return values that flow into subsequent steps. Errors in code blocks are caught and can trigger error handlers.","intents":["I want to transform data between steps without creating a custom piece","I need to write conditional logic that's too complex for the router piece","I want to perform calculations or string manipulations on workflow data"],"best_for":["Developers comfortable with JavaScript who need custom logic","Workflows requiring data transformation not available in pre-built pieces","Teams avoiding the overhead of creating custom pieces for one-off logic"],"limitations":["Sandboxed execution has ~5-second timeout — long-running scripts are terminated","No access to external libraries (npm packages) — only built-in JavaScript","Sandbox cannot make HTTP requests or access the file system","Code is executed synchronously — no async/await support","Debugging is limited to console.log output captured in execution logs"],"requires":["JavaScript knowledge (ES6+)","Access to the code editor in the flow builder","Execution engine with vm2 or similar sandbox library"],"input_types":["JavaScript code string","flow execution context (variables, step outputs)"],"output_types":["code execution result (any JSON-serializable value)","error objects"],"categories":["code-generation-editing","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-activepieces--activepieces__cap_7","uri":"capability://automation.workflow.trigger.based.flow.activation.with.polling.and.webhook.support","name":"trigger-based flow activation with polling and webhook support","description":"Supports multiple trigger types for activating flows: webhook triggers (HTTP POST), polling triggers (periodic checks), and manual triggers (user-initiated). Polling triggers are executed by a scheduler that runs at configured intervals (e.g., every 5 minutes) and checks for new data. Triggers are implemented as pieces that export a trigger interface with a polling function or webhook handler. The flow engine enqueues a new execution for each trigger event.","intents":["I want to run a workflow on a schedule (e.g., every hour, daily, weekly)","I want to trigger a workflow when a specific event occurs in an external system","I want to manually trigger a workflow from the UI for testing or ad-hoc execution"],"best_for":["Scheduled automation use cases (daily reports, periodic syncs)","Event-driven workflows triggered by external systems","Teams testing workflows before deploying to production"],"limitations":["Polling triggers have a minimum interval of 5 minutes (configurable) — more frequent polling requires webhooks","Polling can miss events if the trigger checks less frequently than events occur","Manual triggers require user interaction — cannot be automated","Trigger scheduling is not distributed — all polling runs on a single scheduler instance"],"requires":["Trigger piece configured in the flow","For polling: scheduler service running on at least one server instance","For webhooks: public HTTP endpoint and external service configuration","For manual: user access to the flow UI"],"input_types":["trigger configuration (interval, webhook URL)","external event data"],"output_types":["flow execution job","trigger event data"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-activepieces--activepieces__cap_8","uri":"capability://automation.workflow.flow.versioning.and.deployment.with.git.sync.integration","name":"flow versioning and deployment with git sync integration","description":"Maintains version history for flows, allowing users to view, compare, and revert to previous versions. Flows are stored as JSON definitions in the database with version metadata (timestamp, author, change description). The platform supports git sync, enabling flows to be exported to a git repository and imported back, facilitating version control and CI/CD integration. Deployments can be promoted from development to production environments with approval workflows.","intents":["I want to track changes to my workflows and revert to a previous version if needed","I want to store my workflows in git for version control and code review","I want to promote workflows from development to production with approval gates"],"best_for":["Teams using git-based workflows and CI/CD pipelines","Enterprise deployments requiring change tracking and audit trails","Developers wanting to review flow changes before deployment"],"limitations":["Git sync is one-way (export/import) — no automatic bidirectional sync","Merge conflicts between git and database versions are not automatically resolved","Version history is stored in the database — no distributed version control","Approval workflows are not built-in — require external CI/CD integration"],"requires":["Git repository for storing flow definitions","Git credentials (SSH key or personal access token) configured in Activepieces","Flow definition in JSON format","Database for storing version metadata"],"input_types":["flow definition JSON","git commit metadata"],"output_types":["versioned flow definitions","git commits","deployment status"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-activepieces--activepieces__cap_9","uri":"capability://automation.workflow.billing.and.quota.management.with.usage.tracking","name":"billing and quota management with usage tracking","description":"Implements a quota system that tracks usage metrics (flow executions, data processed, API calls) per user or workspace and enforces limits based on the subscription tier. The billing service records usage events, calculates charges, and prevents execution if quotas are exceeded. Quotas are configurable per plan (free, pro, enterprise) and can be soft limits (warnings) or hard limits (blocking execution). Usage is tracked in real-time via the execution engine and aggregated for billing.","intents":["I want to enforce usage limits on different subscription tiers","I need to track how many workflows each user has executed for billing purposes","I want to prevent users from exceeding their quota without blocking their account"],"best_for":["SaaS platforms monetizing Activepieces usage","Enterprise deployments with chargeback models","Teams needing to control costs by enforcing execution limits"],"limitations":["Quota enforcement is not real-time — there's a delay between execution and quota update","No built-in metering for complex usage patterns (e.g., per-API-call charges)","Quota reset is daily/monthly — no custom billing cycles","No integration with payment processors (Stripe, etc.) — requires custom implementation"],"requires":["Database for storing usage events and quota limits","Billing configuration per subscription tier","Execution engine instrumentation to record usage events","Payment processor integration (custom implementation)"],"input_types":["usage events (execution count, data processed)","subscription tier"],"output_types":["quota status","billing charges","quota exceeded errors"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":43,"verified":false,"data_access_risk":"high","permissions":["Modern browser with ES2020+ support (Chrome 90+, Firefox 88+, Safari 14+)","Activepieces server running with frontend assets served","Active user session with flow edit permissions","TypeScript 4.9+","Node.js 18+ for piece development","Activepieces piece framework package (@activepieces/pieces-framework)","API credentials for the target service","Piece configuration with retry settings","Error handler pieces (log, notify, etc.) for handling failures","Database for storing error logs"],"failure_modes":["Complex conditional logic requires switching to code mode or using router pieces","Large workflows (100+ steps) may experience UI lag due to canvas rendering overhead","No collaborative real-time editing — single user per flow at a time","Pieces are TypeScript-only — no Python, Go, or other language SDKs for custom pieces","Each piece is independently versioned; breaking changes in one piece don't auto-propagate to dependent flows","No built-in rate limiting per piece — relies on downstream API rate limits","Retry logic is per-piece — no global retry strategy across the flow","Exponential backoff is fixed (1s, 2s, 4s, 8s) — not customizable","Max retries are capped at 10 to prevent infinite loops","Errors are not automatically escalated to external monitoring systems","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.3886088960419314,"quality":0.5,"ecosystem":0.6000000000000001,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.3,"quality":0.25,"ecosystem":0.15,"match_graph":0.25,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:21.549Z","last_scraped_at":"2026-05-03T13:56:56.344Z","last_commit":"2026-05-03T13:30:28Z"},"community":{"stars":22021,"forks":3611,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=activepieces--activepieces","compare_url":"https://unfragile.ai/compare?artifact=activepieces--activepieces"}},"signature":"RcW4iDVJ4htTKFKzQnUDpv8c/JmezgzdQg0JeS6uMI+glD7Oa3PrtGbcv1IRzx1WxHDckS9JvLXFy6Up26eBAw==","signedAt":"2026-06-20T03:28:37.968Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/activepieces--activepieces","artifact":"https://unfragile.ai/activepieces--activepieces","verify":"https://unfragile.ai/api/v1/verify?slug=activepieces--activepieces","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"}}