# Workflows Hub Build powerful sequential automation workflows with AgenticFlow's visual drag-and-drop builder. No coding required. ## What are Workflows? Workflows are **linear, sequential automation flows** that execute step-by-step tasks by connecting nodes together. Each workflow: * Executes nodes **one by one, from top to bottom** * Processes data through a **linear chain of nodes** * Integrates with **300+ tools (MCPs)** * Runs **on-demand or on schedule** * Follows a **single execution path** (no branching or loops) ## How Workflows Work ### Core Concepts
Every workflow consists of three main components: **1. Input Schema** (What data does the workflow need?) * Define parameters users provide when starting the workflow * Supports multiple input types: text, numbers, files, dropdowns, JSON, etc. * Each input has a unique name that nodes can reference **2. Nodes** (What processing steps happen?) * The workflow executes nodes **sequentially from top to bottom** * Each node has a unique name (e.g., `web_scraper`, `send_email`) * Each node performs a specific task (API call, data transform, AI generation, etc.) * Nodes reference data using parameter substitution: `{{input_name}}` or `{{node_name.output_field}}` **3. Output Mapping** (What data does the workflow return?) * Define which node outputs to return as final workflow results * Map output fields to node outputs: `{"result": "{{final_node.output}}"}` * **Optional**: If not configured, the workflow automatically returns the last node's output ### Execution Flow Workflows execute in a **strict linear order**: ``` User Inputs → Node 1 → Node 2 → Node 3 → ... → Node N → Workflow Output ``` * **No branching**: Every node executes every time * **No loops**: Nodes run exactly once in sequence * **Top-to-bottom**: Execution order matches visual layout * **Data flows forward**: Later nodes can reference earlier nodes' outputs ### Parameter Substitution Connect data between workflow steps using `{{...}}` syntax: **Reference workflow inputs:** ``` {{user_email}} {{website_url}} {{search_query}} ``` **Reference node outputs:** ``` {{web_scraper.content}} {{llm_analyzer.summary}} {{api_call.response}} ``` **Use in node configurations:** ```json { "email_body": "Here's your analysis: {{llm_analyzer.summary}}", "recipient": "{{user_email}}", "subject": "Results for {{search_query}}" } ``` ### Output Mapping Behavior The workflow's output mapping is **optional** and controls what data is returned: **When Output Mapping IS Defined:** ```json { "summary": "{{analyzer.result}}", "status": "{{email.success}}", "timestamp": "{{current_time.value}}" } ``` * Returns only the specified fields * Can combine outputs from multiple nodes * Gives you full control over the response structure **When Output Mapping IS NOT Defined:** * The workflow automatically returns **all outputs from the last node** * Simpler for workflows where you only care about the final step's result * No need to manually map outputs **Example:** ``` Node 1: fetch_data → {data: [...], count: 10} Node 2: process_data → {processed: [...], errors: []} Node 3: save_results → {success: true, id: "123"} Without output mapping → Returns: {success: true, id: "123"} With output mapping → Returns: Whatever you specify ``` ## When to Use Workflows **Perfect for**: * **Sequential automation**: Step-by-step processes with a clear order * **Data processing pipelines**: Transform data through multiple stages * **API orchestration**: Chain multiple API calls together * **Scheduled tasks**: Run automated processes on a schedule * **Tool integration**: Connect different services in sequence * **Batch operations**: Process data in a predictable, linear way **Use Agents instead when**: * You need conversational interaction * Real-time chat with users * Interactive Q\&A systems * Dynamic decision-making during execution **Use Workforce instead when**: * You need multiple AI agents collaborating * Complex multi-agent orchestration * Dynamic routing between different processing paths *** ## Your First Workflow: A Simple Example Let's build a workflow that scrapes a website and sends the content via email. ### Step 1: Define Inputs ```json { "website_url": { "type": "string", "title": "Website URL", "description": "URL to scrape" }, "recipient_email": { "type": "string", "title": "Email", "description": "Where to send results" } } ``` ### Step 2: Add Nodes (Top to Bottom) **Node 1: `web_scraper`** (Scrape the website) * Node type: `web_scraping` * Input config: `{"url": "{{website_url}}"}` **Node 2: `send_email`** (Email the content) * Node type: `send_email` * Input config: ```json { "recipient": "{{recipient_email}}", "subject": "Website Content", "body": "{{web_scraper.content}}" } ``` ### Step 3: Define Output (Optional) **Option A: Custom Output Mapping** ```json { "status": "{{send_email.success}}", "content": "{{web_scraper.content}}" } ``` **Option B: No Output Mapping** * If you don't define output mapping, the workflow automatically returns the output from the last node (`send_email`) ### Execution When you run this workflow: 1. User provides `website_url` and `recipient_email` 2. `web_scraper` node executes, scrapes the URL, outputs `content` 3. `send_email` node executes, sends email with scraped content 4. **Workflow returns**: * With custom mapping: `status` and `content` fields * Without mapping: All outputs from `send_email` node *** ## Getting Started ### [Workflows Quickstart](https://docs.agenticflow.ai/get-started/workflows-quickstart) Build your first workflow in 10 minutes. ### [Data Flow & Type Handling](https://docs.agenticflow.ai/workflows/data-flow-and-types) **Essential guide** to how data flows between nodes and handling data types correctly. Learn how to reference data and avoid type mismatch errors. *** ## Workflow Building Blocks ### [User Inputs](https://github.com/PixelML/agenticflow-docs/blob/main/docs/04-workflows/building-blocks/user-inputs/README.md) Collect data to start your workflow: * Text Input * Number Input * File Upload * Date/Time Picker * Dropdown Select * Checkbox * Multi-select * Email Input * URL Input * Phone Input * JSON Input * Rich Text Editor ### [Variables](https://docs.agenticflow.ai/workflows/variables) Manage constants, configuration, and secrets across your project: * **Project Variables** - Global values shared across workflows * **Workflow Variables** - Local configuration for a single workflow * **System Variables** - Auto-injected runtime context (User ID, Workflow ID) * **Secret Management** - Secure storage for API keys and tokens ### [Actions](https://github.com/PixelML/agenticflow-docs/blob/main/docs/04-workflows/building-blocks/actions/README.md) Execute tasks and operations: * **AI/LLM Actions** - AI model calls, text generation, embeddings * **Data Processing** - Transform, filter, aggregate data * **Integrations** - Connect to 300+ tools via MCPs * **API Calls** - HTTP requests, webhooks * **Database** - Read/write operations * **File Operations** - Upload, download, process files * **Notifications** - Email, Slack, SMS * **Data Transformation** - Format, parse, convert data ### [Logic & Control](https://github.com/PixelML/agenticflow-docs/blob/main/docs/04-workflows/building-blocks/logic/README.md) Control workflow execution: * **Error Handling** - Handle failures gracefully * **Delays** - Wait for time or conditions * **Data Validation** - Verify data meets requirements ### [Outputs](https://github.com/PixelML/agenticflow-docs/blob/main/docs/04-workflows/building-blocks/outputs/README.md) Return results and data: * Display results * Return JSON * Download files * Send notifications * Trigger webhooks * Store in database *** ## Advanced Features ### Error Handling Handle failures gracefully: * Try/catch blocks * Retry logic * Fallback actions * Error notifications *** ## Workflow Templates Start with pre-built workflow templates: ### [Browse All Templates](https://docs.agenticflow.ai/workflows/templates) **Popular Templates**: * Data Processing Pipeline * Email Automation * Lead Qualification * Report Generation * Content Publishing * File Processing * API Integration * Notification System * Data Synchronization * Scheduled Batch Jobs *** ## Workflow Patterns ### Common Automation Patterns **Sequential Processing** (Basic linear flow): ``` Input → Process → Transform → Output ``` **Multi-Step Data Pipeline**: ``` Input → Fetch Data → Transform → Enrich → Validate → Store → Output ``` **AI Analysis Chain**: ``` Input → Extract Text → Analyze with LLM → Summarize → Format → Output ``` **API Integration Flow**: ``` Input → Call API 1 → Parse Response → Call API 2 → Combine Results → Output ``` **Content Generation Pipeline**: ``` Input → Research → Generate Draft → Review → Format → Publish → Output ``` *** ## Best Practices ### Workflow Design Best Practices **Design Principles**: * Keep workflows focused and modular * Use clear node names * Add comments and documentation * Handle errors gracefully * Test edge cases **Performance**: * Minimize AI calls (they're slower and cost more) * Reduce unnecessary nodes in the chain * Cache data when possible * Keep workflows focused and concise **Maintainability**: * Use parameter substitution for flexibility * Avoid hardcoding values * Document complex logic * Version control your workflows **Error Handling**: * Always handle API failures * Provide fallback options * Log errors for debugging * Notify on critical failures *** ## Node Reference AgenticFlow provides **193+ workflow nodes** across categories: * **AI & LLM** (20+ nodes) - Text generation, embeddings, vision * **Data** (30+ nodes) - Transform, filter, aggregate, validate * **Integrations** (300+ MCPs) - Connect to external tools * **Logic** (15+ nodes) - Conditionals, loops, branches * **HTTP** (10+ nodes) - API calls, webhooks, requests * **Files** (12+ nodes) - Upload, download, process, convert * **Database** (15+ nodes) - SQL, NoSQL operations * **Text** (20+ nodes) - String operations, parsing, formatting * **Math** (10+ nodes) - Calculations, statistics * **Date/Time** (8+ nodes) - Date operations, scheduling * **Notifications** (10+ nodes) - Email, Slack, SMS, push * **Utilities** (40+ nodes) - Various helper functions See [Complete Node Reference](https://docs.agenticflow.ai/reference/nodes) for all 193+ nodes. *** ## Testing & Debugging ### Testing Your Workflow 1. Start with sample data 2. Run step-by-step 3. Inspect node outputs 4. Test error cases 5. Verify edge cases 6. Performance testing ### Debugging Tools * Node output inspection * Execution logs * Error messages * Variable inspection * Step-through execution *** ## Deployment & Scheduling ### Execution Options * **Manual** - Run on-demand via UI or API * **Scheduled** - Cron-based scheduling * **Triggered** - Webhook or event-based * **API** - Call via REST API * **Embedded** - Integrate in applications ### Monitoring * Execution history * Success/failure rates * Performance metrics * Credit consumption * Error tracking *** ## Integrations Connect workflows to 300+ tools via MCPs: ### Popular Workflow Integrations * **Data Sources**: Google Sheets, Airtable, Databases * **Communication**: Gmail, Slack, Discord, Telegram * **CRM**: Salesforce, HubSpot, Pipedrive * **Storage**: Google Drive, Dropbox, S3 * **APIs**: Custom HTTP requests * **Databases**: PostgreSQL, MongoDB, MySQL See [All Integrations](https://docs.agenticflow.ai/integrations/07-integrations) *** ## Troubleshooting Common issues and solutions: * **Workflow fails**: Check node connections and required inputs * **Slow execution**: Optimize node count and parallel processing * **Integration errors**: Verify MCP credentials and permissions * **Data issues**: Validate input formats and transformations * **Timeout errors**: Split long-running tasks, increase limits See [Troubleshooting Guide](https://docs.agenticflow.ai/support/troubleshooting) for more help. *** ## Workflows vs Workforce vs Agents **Use Workflows when**: * You need **linear, sequential automation** * Single execution path from start to finish * Connecting tools and APIs in a predictable order * Scheduled or triggered batch processing * Data pipelines with fixed steps **Use Agents when**: * You need **conversational interaction** * Real-time chat with users * Dynamic decision-making during conversations * Interactive Q\&A and assistance **Use Workforce when**: * You need **multiple AI agents collaborating** * Complex multi-agent orchestration * Dynamic routing between different agents * Advanced coordination patterns See [Workforce Documentation](https://docs.agenticflow.ai/workforce/05-workforce) *** ## Related Documentation * [Agents](https://docs.agenticflow.ai/ai-agents/03-agents) - For conversational AI * [Workforce](https://docs.agenticflow.ai/workforce/05-workforce) - For multi-agent systems * [Integrations](https://docs.agenticflow.ai/integrations/07-integrations) - Available MCPs * [Node Reference](https://docs.agenticflow.ai/reference/nodes) - All 193+ nodes * [API Reference](https://github.com/PixelML/agenticflow-docs/blob/main/docs/09-developers/api/endpoints/workflows.md) - Workflow API *** ## Learn More * [AgenticFlow 101](https://docs.agenticflow.ai/learn/courses/agenticflow-101) - Foundation course * [Video Tutorials](https://github.com/PixelML/agenticflow-docs/blob/main/docs/02-learn/video-tutorials/README.md) - Visual learning * [Use Cases](https://docs.agenticflow.ai/use-cases/10-use-cases) - Real-world examples * [Community](https://docs.agenticflow.ai/support/community) - Ask questions *** **Ready to build your first workflow?** [Start the Quickstart →](https://docs.agenticflow.ai/get-started/workflows-quickstart)