Streamline complex multi-agent cybersecurity workflows with minimal code and maximum capability through declarative JSON configurations
Enhanced Agents revolutionizes AI agent orchestration for cybersecurity by replacing hundreds of lines of Python code with simple JSON configurations
Enhanced Agents is a groundbreaking GitHub project that provides a revolutionary approach to AI agent orchestration for cybersecurity operations. Unlike frameworks like LangChain that require extensive Python coding, Enhanced Agents allows you to orchestrate complex multi-agent cybersecurity workflows using simple JSON configurations.
Key Innovation: What would take 500+ lines of Python code in LangChain can be achieved with ~300 lines of JSON configuration, dramatically reducing development time and complexity.
Modular design with lightweight core and optional power-ups for enterprise needs
Lightweight Foundation
Enterprise Extensions
JSON-Driven Execution
Real-world example: Multi-stage security analysis pipeline with dynamic decision-making
Why Enhanced Agents is revolutionizing AI agent development in cybersecurity
Define entire multi-agent workflows in JSON instead of writing complex Python code. No callbacks, no complex error handling - just configuration.
Lightweight core with optional components. Include only what you need - SQL tools, HTTP clients, vector databases, or planning algorithms.
Built-in support for structured data (SQL), unstructured data (vectors), and hybrid workflows. Perfect for enterprise scenarios mixing databases and AI.
Agents can make decisions and trigger different workflows based on data. Conditional logic without complex programming.
SQLite-backed memory system automatically shares context between agents without requiring vector embeddings for structured data.
From concept to deployment in minutes. Interactive CLI for testing and one-command execution for production workflows.
How Enhanced Agents compares to popular alternatives
| Feature | LangChain | AutoGen | CrewAI | Enhanced Agents |
|---|---|---|---|---|
| Configuration Method | Python Code | Python Classes | Python Scripts | JSON Configuration |
| Learning Curve | High | Medium | Medium | Low |
| Enterprise Data Support | Manual Setup | Limited | Limited | Built-in SQL/Vector |
| Memory Management | Multiple Options | Conversation Based | Basic | Automatic SQLite |
| Workflow Branching | Manual Coding | Agent Conversations | Code Required | Declarative Logic |
| Code Complexity | 500+ lines | 200+ lines | 150+ lines | ~50 lines JSON |
Real-world cybersecurity applications where Enhanced Agents excels
Understanding the components that make Enhanced Agents powerful yet simple for cybersecurity workflows
Central orchestrator that creates and executes agents based on JSON workflow definitions. Handles the entire agent lifecycle from initialization to completion.
Specialized agent that can make decisions and branch workflows. Enables conditional logic without complex programming - agents choose their next actions based on data.
Persistent SQLite-backed storage for sharing context between agents. Automatically provides relevant context without requiring vector embeddings for structured data.
Handles structured output parsing with schema validation. Ensures agents return properly formatted JSON or markdown with automatic retries and validation.
From installation to your first multi-agent cybersecurity workflow in minutes
Download Enhanced Agents from GitHub and install dependencies with a single command.
Define your agent workflow in JSON - specify agents, prompts, tools, and memory requirements.
Include optional components like SQL tools, HTTP clients, or vector databases as needed for your use case.
Run your workflow with a single command. Scale from simple sequences to complex enterprise pipelines.
The benefits that make Enhanced Agents the future of AI orchestration
Reduce development time from weeks to hours. Transform complex multi-agent scenarios into simple JSON configurations. No more debugging intricate Python chains or managing callback systems.
JSON workflows are self-documenting and easy to modify. Non-developers can understand and adjust agent behavior. Version control becomes trivial with declarative configurations.
Built-in support for enterprise data sources. Direct SQL integration for structured data, vector search for unstructured content. No additional infrastructure required.
Use the right tool for each job - SQL for structured queries, LLMs for reasoning, vectors only when needed. Efficient resource utilization without over-engineering.
Join the Enhanced Agents community and contribute to the future of AI orchestration
Access the complete Enhanced Agents framework, documentation, and examples. Contribute to the project and help shape the future of declarative AI orchestration.
Explore RepositoryComprehensive guides, API references, and examples to get you started quickly with Enhanced Agents.
Real-world examples including cybersecurity analysis, customer journey mapping, and business intelligence pipelines.
Join discussions, share use cases, and collaborate with other developers building the next generation of AI applications.
Transform complex multi-agent cybersecurity orchestration into simple JSON configurations. Experience the future of cybersecurity AI development with Enhanced Agents.