Agents Quickstart
Complete guide to AgenticFlow's advanced agent system - based on actual code implementation
New to AgenticFlow? This guide covers the actual agent system as implemented in the platform - it's more sophisticated than typical AI chatbots.
What Makes AgenticFlow Agents Different?
Unlike simple chatbots, AgenticFlow agents are enterprise-grade AI workers with:
300+ Tool Integrations via MCP (Model Context Protocol)
Advanced Knowledge Management with hybrid search (10-file limit per agent)
Task Management System built-in for tracking work
Sub-Agent Architecture for delegation and specialization
Workflow Integration - agents can execute custom automations
Webhook Triggers for enterprise system integration
Voice Input with speech-to-text capabilities
File System Memory for persistent context
Creating Your First Agent (3 minutes)
AgenticFlow uses a "create-then-configure" approach rather than a wizard.
Step 1: Initial Creation
Click "Agents" in the left sidebar
Click "New Agent", then click "from scratch"
Fill out basic info:
Name: Choose a clear, descriptive name
Description: Optional, for your reference
Click "Create Agent"
The agent is created with defaults:
Model:
agenticflow/gpt-4o-miniTemperature: 0.1
Welcome message: "Hello, how can I help you today?"
Private visibility
Step 2: Configuration Interface
After creation, you'll see 20 configuration tabs. This is where the real power lies:
Core Configuration
1. Basic Information
Avatar Selection: Built-in avatar picker or upload custom
Voice Input: Enable speech-to-text for conversations
Description: Update anytime
2. AI Model Configuration
Available Models:
Multiple providers: OpenAI, Google Gemini, Anthropic Claude
Automatic provider connection setup
Welcome credits for PixelML provider
Advanced Parameters:
Temperature: 0-1 creativity slider (default: 0.1)
Max Output Tokens: 2000-50000 (optional, default: unlimited)
Max Input Tokens: 2000-50000 (optional, default: unlimited)
3. System Prompt (Most Important)
Rich Markdown Editor with formatting support
Auto-save to prevent data loss
This defines your agent's personality and capabilities
Template System Prompt:
Advanced Features (Where AgenticFlow Shines)
4. Knowledge Integration (RAG System)
Text Knowledge (Up to 10 files per agent):
Search Types: Hybrid (default), Semantic, Full-text
Advanced Settings:
Top K: 1-10 results (default: 5)
Threshold: 0-1 similarity (default: 0.2)
Query Rewrite: AI query optimization (default: on)
Reranking: Result reranking (default: off)
Auto-retrieval: Automatic knowledge search
Table Knowledge:
Structured data integration
Queryable datasets
5. MCP Tool Integrion (300+ Connectors)
Model Context Protocol (MCP) provides access to:
Connected MCP Servers: Workspace-level integrations
Registry Servers: Platform-wide tool library
Per-Tool Configuration:
Custom Description: How agent sees the tool
Run Behavior:
Auto-run (agent decides when to use)
Request Confirmation (asks user first)
Timeout: 1-300 seconds (default: 150)
Tool Selection: Enable/disable specific tools within each MCP server
Tool Categories Available:
AI & ML Services
Business Management & CRM
Communication (Email, Slack, SMS)
Data Analytics & Databases
Developer Tools & APIs
E-commerce & Payments
Marketing & Social Media
Productivity & Project Management
6. Workflow Integration (Custom Automation)
Agents can execute your custom workflows as tools:
Workflow Selection: Choose from workspace workflows
Tool Configuration:
Description: How the agent sees this workflow
Run Behavior: Auto-run vs Request Confirmation
Timeout: Execution time limit
Input Override: JSON parameter customization
Connection Detection: Automatically identifies missing connections
7. Sub-Agent System
Hierarchical Architecture: Agents can manage other agents
Delegation: Route specialized queries to expert sub-agents
Coordination: Master agent orchestrates multiple specialists
8. Task Management
Built-in task system for agents:
Task States: Pending, In Progress, Completed, Cancelled, Blocked, Deferred
Priority Levels: Low, Medium, High
Context Tracking: Tasks linked to conversations
9. File System Tools
Memory Persistence: Agents can read/write files
Session Context: Maintain context across conversations
Document Management: Handle and reference files
10. Advanced Chat Features
Message Management:
Suggested Messages: Pre-defined conversation starters
Welcome Message: Custom greeting
Auto-suggestions: AI-powered response suggestions
Chat Theming:
Color Themes: Default, Orange, Blue, Green, Yellow, Violet
Font Sizes: Small, Medium, Large
Branding: Hide/show "Powered by" attribution
11. Webhook Triggers (Enterprise Integration)
External System Integration:
HTTP Methods: GET, POST, PUT, DELETE
Authentication: None, Basic Auth, Bearer Token
Response Codes: Configurable success handling
Custom Endpoints: Unique webhook URLs per agent
Testing Your Agent
Chat Interface Features
Once configured, your agent supports:
Streaming Responses: Real-time message generation
Multimodal Input: Text, voice, file uploads
Tool Execution: Visual previews of tool calls
Thread Management: Conversation persistence
Anonymous Access: Public agents work without login
What Should Happen
Natural Conversation: Agent responds according to system prompt
Tool Usage: Agent automatically uses connected tools when relevant
Knowledge Retrieval: Searches knowledge base when needed
Task Creation: Can create and track tasks if enabled
Deployment Options
Publishing Levels
Private: Only you can access
Public: Listed in public directory
Public Visible: Accessible by direct link only
Integration Options
Embed Code: JavaScript widget for websites
API Access: RESTful agent interaction
Webhook Endpoints: External system triggers
Sharing Features
Embeddable Chat: Custom-branded chat widgets
Direct Links: Share agent access links
Template Creation: Convert agent to reusable template
Pro Tips for Building Effective Agents
1. Start Simple, Then Expand
Begin with basic chat functionality
Add tools one at a time
Test each addition thoroughly
2. Optimize Knowledge Base
Use the 10-file limit strategically
Choose high-quality, relevant documents
Adjust search parameters based on testing
3. Tool Configuration Strategy
Start with auto-run disabled for new tools
Enable auto-run only after testing
Use descriptive tool names for better AI understanding
4. System Prompt Best Practices
Be specific about the agent's role and capabilities
Include examples of good responses
Set clear boundaries and limitations
Update based on real conversations
5. Performance Monitoring
Review chat logs regularly
Monitor tool usage patterns
Adjust configuration based on user feedback
Understanding Costs
AgenticFlow uses a bucket-based credit system:
Base Cost: ~4.0 credits per conversation turn
Tool Usage: Additional costs for external API calls
Model Costs: GPT-4 costs more than GPT-3.5
Knowledge Retrieval: Included in base cost
File Processing: May incur additional charges
Credit Sources:
Subscription plans (with monthly credit buckets)
One-time top-ups (non-expiring)
Promotional credits
Welcome credits (for new users)
Troubleshooting Common Issues
Agent Not Responding
Check workspace credit balance
Verify model configuration
Ensure system prompt isn't empty
Tools Not Working
Check MCP server connection status
Verify tool permissions and authentication
Review timeout settings
Knowledge Base Issues
Ensure files are properly uploaded (max 10 per agent)
Check search threshold settings
Verify file format compatibility
Performance Problems
Reduce knowledge base size if responses are slow
Adjust temperature for more consistent responses
Consider switching to faster model (GPT-3.5 vs GPT-4)
What's Next?
Once you have a working agent:
Explore Templates: Browse pre-built agents for inspiration
Add MCP Integrations: Connect to your favorite tools and services
Create Workflows: Build custom automation sequences
Set Up Webhooks: Integrate with external systems
Build Sub-Agents: Create specialized agent teams
Advanced Features to Explore:
Multi-agent conversations
Workflow orchestration
Enterprise webhook integrations
Custom knowledge base optimization
Task management workflows
Getting Help
Need Assistance?
Discord Community: https://qra.ai/discord - Real-time help
Documentation: Browse related guides
Support Email: [email protected]
Feature Requests: https://agenticflow.featurebase.app/
🎨 Visual Guides:
Agents Hub - Complete agent configuration guide
Workflows Hub - Drag-and-drop workflow creation
Workforce Hub - Multi-agent team orchestration
Related Guides:
Workflows Quickstart - Build custom automation
MCP Integration Guide - Connect external tools
Key Concepts - Understanding the platform
🎉 Congratulations! You now understand AgenticFlow's sophisticated agent system. Unlike simple chatbots, you can build enterprise-grade AI workers that integrate with hundreds of tools, manage tasks, and orchestrate complex workflows.
Questions? Join our Discord - we're here to help you build amazing AI agents!
Last updated