# Compozy

## Docs

- [Authentication](https://docs.compozy.ai/cli/authentication.md): Authentication in Compozy is required to access cloud services, publish components to the registry, and manage your workflows in production. This guide covers how to authenticate with Compozy Cloud and manage your credentials securely.
- [Components](https://docs.compozy.ai/cli/components.md): Commands for managing components in your Compozy project
- [Dependencies](https://docs.compozy.ai/cli/dependencies.md): Learn how to manage dependencies in your Compozy project
- [Development](https://docs.compozy.ai/cli/dev-tools.md): Commands for managing your Compozy project
- [CLI Overview](https://docs.compozy.ai/cli/overview.md): The Compozy CLI is a powerful command-line interface that enables you to build, test, and deploy AI workflows with ease. Learn how to use its core features to streamline your development process.
- [Project](https://docs.compozy.ai/cli/project.md): Common commands for managing your Compozy project
- [Project Configuration](https://docs.compozy.ai/cli/project-configuration.md): Configure the Compozy CLI and manage global settings
- [Registry](https://docs.compozy.ai/cli/registry.md): Commands for managing the Compozy registry
- [API Reference](https://docs.compozy.ai/core/agents/api.md): Learn about the parameters and definitions of agents in Compozy.
- [Create & Publish](https://docs.compozy.ai/core/agents/creating.md): Learn how to create and publish your agents to the Compozy registry.
- [Examples](https://docs.compozy.ai/core/agents/examples.md): Real-world examples of using agents in Compozy.
- [Agents](https://docs.compozy.ai/core/agents/overview.md): Learn about agents in Compozy and how they extend workflow capabilities.
- [Usage](https://docs.compozy.ai/core/agents/usage.md): Agents in Compozy are defined and configured using the following structure and patterns.
- [API Reference](https://docs.compozy.ai/core/base-structure/api.md): Complete API reference for Compozy base structure configuration.
- [Authors](https://docs.compozy.ai/core/base-structure/authors.md): Author configuration in Compozy provides a standardized way to document workflow ownership, maintenance responsibilities, and collaboration details. This information helps users understand who to contact for support, contributions, and updates.
- [Base structure](https://docs.compozy.ai/core/base-structure/overview.md): Compozy workflows are defined in YAML files that configure AI agents, tools, and data processing. This page covers the key properties of workflow configurations.
- [Triggers](https://docs.compozy.ai/core/base-structure/triggers.md): Triggers define how and when workflows start executing. They specify the entry point for your workflow and define the schema for input data. Compozy supports several types of triggers to accommodate different use cases and integration needs.
- [API Reference](https://docs.compozy.ai/core/mcp/api.md): Learn about the parameters and definitions of MCP servers in Compozy.
- [Examples](https://docs.compozy.ai/core/mcp/examples.md): Real-world examples of using MCP servers in Compozy.
- [Model Context Protocol](https://docs.compozy.ai/core/mcp/overview.md): Model Context Protocol (MCP) is a standardized way to connect your Compozy workflows with external services and communication channels. It acts as a bridge that maintains context, memory, and state across different interactions, enabling more intelligent and contextual automation.
- [Usage](https://docs.compozy.ai/core/mcp/usage.md): MCP servers are defined and implemented using the following structure and patterns.
- [API Reference](https://docs.compozy.ai/core/memory/api.md): Learn about the parameters and definitions of memory in Compozy.
- [Memory](https://docs.compozy.ai/core/memory/overview.md): Memory in Compozy is a powerful feature that enables workflows, tasks, and agents to maintain context and recall information from past interactions.
- [Memory Types](https://docs.compozy.ai/core/memory/types.md): Memory in Compozy comes in various types, each designed for specific use cases and deployment scenarios. Understanding these types helps in choosing the right solution for your needs.
- [Usage](https://docs.compozy.ai/core/memory/usage.md): Memory in Compozy is defined and configured using the following structure and patterns.
- [API Reference](https://docs.compozy.ai/core/tasks/api.md): Complete API reference for Compozy tasks, including all task types, configurations, and event handlers.
- [Create & Publish](https://docs.compozy.ai/core/tasks/creating.md): Repository-based tasks are standalone projects that can be published and shared with other Compozy users. You can create tasks using YAML configuration files that define the task's metadata, schema, and execution flow.
- [Tasks](https://docs.compozy.ai/core/tasks/overview.md): Tasks are the building blocks of Compozy, representing both individual units of work and flow control that can be executed, monitored, and orchestrated.
- [Task Types](https://docs.compozy.ai/core/tasks/types.md): Tasks in Compozy come in various types, each designed for specific use cases and execution patterns. Understanding these types is crucial for building efficient and maintainable automations.
- [Usage](https://docs.compozy.ai/core/tasks/usage.md): Tasks in Compozy are defined and configured using the following structure and patterns.
- [Custom Dependencies](https://docs.compozy.ai/core/template-engine/custom-dependencies.md): Learn how to add and use custom JavaScript libraries in your template expressions for data manipulation and transformation.
- [Template engine](https://docs.compozy.ai/core/template-engine/overview.md): The template engine in Compozy uses Jinja2-style syntax with JavaScript expressions, allowing you to reference and manipulate data throughout your workflows.
- [Template Functions](https://docs.compozy.ai/core/template-engine/template-functions.md): Compozy leverages popular JavaScript libraries to provide a comprehensive set of utility functions for data manipulation within your template expressions.
- [API Reference](https://docs.compozy.ai/core/tools/api.md): Learn about the parameters and definitions of tools in Compozy.
- [Create & Publish](https://docs.compozy.ai/core/tools/creating.md): Learn how to create and publish your tools to the Compozy registry.
- [Examples](https://docs.compozy.ai/core/tools/examples.md): Real-world examples of using tools in Compozy.
- [Overview](https://docs.compozy.ai/core/tools/overview.md): Learn about tools in Compozy and how they extend workflow capabilities.
- [Usage](https://docs.compozy.ai/core/tools/usage.md): Tools are defined using the following structure:
- [API Reference](https://docs.compozy.ai/core/workflows/api.md): Complete API reference for Compozy workflows configuration.
- [Composability](https://docs.compozy.ai/core/workflows/composability.md): Learn how to break down and compose Compozy workflows into reusable pieces.
- [Create & Publish](https://docs.compozy.ai/core/workflows/creating.md): Repository-based workflows are standalone projects that can be published and shared with other Compozy users. Workflows are defined using YAML configuration files that specify a series of tasks and their relationships.
- [Examples](https://docs.compozy.ai/core/workflows/examples.md): Explore practical examples of Compozy workflows for common use cases.
- [Workflows](https://docs.compozy.ai/core/workflows/overview.md): Workflows in Compozy are like a smart assembly line for your automation needs. They coordinate multiple operations, handle errors gracefully, and ensure your processes run smoothly and predictably.
- [Usage](https://docs.compozy.ai/core/workflows/usage.md): Workflows in Compozy are defined using YAML configuration files. Each workflow consists of tasks and configuration that work together to automate your processes.
- [Cloud Configuration](https://docs.compozy.ai/deployment/cloud/configuration.md): Configure your Compozy Cloud deployment settings, resources, and scaling options
- [Getting Started](https://docs.compozy.ai/deployment/cloud/getting-started.md): Deploy your workflows to Compozy Cloud - the fastest way to get your workflows running in production
- [Cloud Monitoring](https://docs.compozy.ai/deployment/cloud/monitoring.md): Monitor your workflows, view logs, and manage resources in Compozy Cloud
- [Environment Management](https://docs.compozy.ai/deployment/configuration/environments.md): Manage different environments for your Compozy deployments
- [Scaling Configuration](https://docs.compozy.ai/deployment/configuration/scaling.md): Configure auto-scaling, resource limits, and performance settings for your deployments
- [Managing Secrets](https://docs.compozy.ai/deployment/configuration/secrets.md): Securely manage secrets and sensitive information in your deployments
- [Docker Deployment](https://docs.compozy.ai/deployment/self-hosted/docker.md): Deploy Compozy workflows using Docker containers
- [Kubernetes Deployment](https://docs.compozy.ai/deployment/self-hosted/kubernetes.md): Deploy and orchestrate Compozy workflows on Kubernetes clusters
- [Self-Hosted Deployments](https://docs.compozy.ai/deployment/self-hosted/overview.md): Learn about deploying Compozy workflows on your own infrastructure
- [Cloud Providers](https://docs.compozy.ai/deployment/self-hosted/providers.md): Deploy Compozy workflows on AWS, DigitalOcean, GCP, and other cloud providers
- [Core Components](https://docs.compozy.ai/getting-started/core-components.md): Explore the key building blocks of Compozy that work together to create powerful AI automation workflows:
- [Deploying](https://docs.compozy.ai/getting-started/deploying.md): Deploying AI workflows to production requires careful consideration of infrastructure, scaling, and maintenance. Compozy provides multiple deployment options to ensure your workflows run reliably and efficiently in any environment.
- [Integrations](https://docs.compozy.ai/getting-started/integrations.md): Compozy seamlessly integrates with your existing tech stack, offering enterprise-grade connections to popular tools and services. Our integration ecosystem helps you maintain security, scalability, and operational excellence.
- [Project Management](https://docs.compozy.ai/getting-started/project-management.md): Learn how to effectively manage your Compozy projects using the CLI.
- [Quickstart](https://docs.compozy.ai/getting-started/quickstart.md): Build your first AI workflow with Compozy in 5 minutes
- [Registry](https://docs.compozy.ai/getting-started/registry.md): Compozy Registry is where AI development meets community collaboration. This initiative is designed to create an open, vibrant marketplace where developers can share, discover, and utilize AI components to accelerate their development process.
- [Welcome to Compozy](https://docs.compozy.ai/getting-started/welcome.md): Compozy is a platform that enables you to build, compose, and share AI agents through a declarative YAML workflow system with powerful context management.
- [CI/CD](https://docs.compozy.ai/integrations/cicd.md): Continuous Integration and Deployment integrations for Compozy
- [Infrastructure](https://docs.compozy.ai/integrations/infrastructure.md): Manage and automate your Compozy infrastructure with popular IaC and automation tools
- [Metrics & Analytics](https://docs.compozy.ai/integrations/metrics.md): Track and analyze your Compozy workflow performance with powerful analytics tools
- [Security](https://docs.compozy.ai/integrations/security.md): Secure your Compozy workflows with enterprise-grade security integrations
- [Telemetry](https://docs.compozy.ai/integrations/telemetry.md): Monitor, track, and analyze your Compozy workflows with integrated telemetry solutions
- [Agents](https://docs.compozy.ai/registry/agents.md): Browse and discover AI agents available in the Compozy registry
- [MCP Servers](https://docs.compozy.ai/registry/mcp-servers.md): List of supported MCP servers available through Compozy registry
- [Tools](https://docs.compozy.ai/registry/tools.md): Browse and discover tools available in the Compozy registry

## OpenAPI Specs

- [openapi](https://docs.compozy.ai/api-reference/openapi.json)