Activepieces

Activepieces is an open‑source, self‑hostable automation engine that replaces tools like Zapier and n8n while adding AI‑first capabilities. At its core, the platform exposes a type‑safe pieces framework written in TypeScript, allowing developers to author reusable integration modules (“pieces”) as npm packages. These pieces are automatically exposed as MCP (Machine‑Controlled Plugins), making them consumable by large language models in applications such as Claude Desktop, Cursor, or Windsurf. The builder is a low‑code canvas that supports loops, branches, auto‑retries, HTTP actions, and code execution with hot reloading for local development.

• Runtime: Node.js (v18+) with a lightweight Express‑based API layer.
• Language: All core logic and pieces are authored in TypeScript, leveraging static typing for compile‑time safety.
• Database: PostgreSQL (via Prisma ORM) stores flow definitions, execution logs, user data, and piece metadata.
• Containerization: Docker images are provided for quick deployment; the service can run behind a reverse proxy (NGINX/Traefik).
• Extensibility: Pieces are published to npm and can be loaded dynamically at runtime; hot‑reload hooks enable live development without restarting the host.
• Security: The platform is SOC 2 Type II compliant and can be network‑gapped for on‑premise deployments, ensuring data does not leave the corporate firewall.

• Flow Builder: Drag‑and‑drop canvas with versioning, conditional logic, and error handling.
• Piece API: Each piece exposes a declarative schema (input, output) and an execution function; developers can expose custom HTTP endpoints or scheduled jobs.
• AI SDK: Built‑in support for OpenAI, Claude, and other LLMs; pieces can invoke the SDK to generate code or prompts.
• Human‑in‑the‑Loop: Built‑in triggers such as “Chat Interface” and “Form Interface” allow workflows to pause for manual approval or data entry.
• Tables: A lightweight relational store (similar to Google Sheets) that can be queried and updated via pieces.
• MCP Server: Pieces are automatically exposed as MCP services, enabling external LLMs to call them as part of a larger agent workflow.

Activepieces is designed for self‑hosting on any infrastructure that supports Docker or a Node runtime. A single container runs the API, while PostgreSQL can be bundled in another container or provisioned via a managed database. The architecture scales horizontally by adding more worker nodes; the event queue is backed by Redis (optional) for distributed execution. Kubernetes manifests are available in the repo, making it straightforward to deploy on cloud providers or on‑prem clusters.

• Plugin System: Developers publish pieces as npm packages; the platform automatically discovers and registers them.
• Webhooks: Each flow can expose an HTTP endpoint that triggers the execution of a specific workflow.
• SDK Hooks: Pieces can register custom actions, triggers, or data connectors through the SDK.
• Embedding: The builder can be embedded in external applications via an iframe, enabling “no‑code” automation inside SaaS products.

Activepieces offers a rich developer portal with comprehensive documentation, code samples, and a community Discord channel. Hot‑reloading eliminates the need for full restarts during piece development, and the type‑safe API surface reduces runtime errors. The platform’s modular design means you can contribute a single piece and instantly make it available to the entire ecosystem, fostering rapid iteration.

• Enterprise Automation: Build secure, on‑prem data pipelines that integrate internal services (CRM, ERP) with external APIs while keeping data within the corporate network.
• AI Agent Orchestration: Combine LLMs with custom pieces to create autonomous agents that can read, write, and approve business documents.
• No‑Code Builders for Clients: Deploy the builder in a sandboxed environment where business users can create workflows without touching code, while developers maintain the underlying pieces.
• Hybrid Human‑AI Workflows: Use human input triggers to pause an AI‑driven process for manual review, ensuring compliance and auditability.

• Performance & Flexibility: Lightweight Node runtime with TypeScript offers fast execution and strong typing, outperforming heavier Python‑based alternatives.
• Licensing: MIT license guarantees freedom to modify and redistribute, unlike proprietary Zapier or paid n8n tiers.
• AI‑First Design: Native LLM integration and an MCP server enable seamless agent creation, a feature absent in many competitors.
• Community‑Driven Ecosystem: With 60 % of pieces contributed by the community and an active npm presence, developers can tap into a growing library without vendor lock‑in.
• Security: Full self‑hosting and SOC 2 compliance make it suitable for regulated industries that cannot expose