MervinPraison/PraisonAI

PraisonAI 🦞 — Hire a 24/7 AI Workforce. Stop writing boilerplate and start shipping autonomous self-improving agents that research, plan, code, and execute tasks. Deployed in 5 lines of code with built-in memory, RAG, and support for 100+ LLMs.

What it solves

PraisonAI provides a streamlined way to build and deploy autonomous AI agents and multi-agent teams. It eliminates the need for extensive boilerplate code, allowing users to create agents that can research, plan, and execute tasks across various applications, from simple scripts to full-scale organizational workforces.

How it works

Users can define agents using a Python SDK, a CLI, or no-code YAML configurations. The system supports a wide range of LLM providers (over 100) and integrates with the Model Context Protocol (MCP) for tool use. It offers multiple interfaces for interaction, including a visual drag-and-drop flow builder (Flow), a management dashboard (Claw), and a clean chat UI.

Who it’s for

It is designed for developers who want to quickly deploy AI agents for research, code generation, content creation, data pipelines, and customer support, as well as non-developers who can use YAML or visual builders to automate business processes.

Highlights

  • Multi-Agent Orchestration: Support for sequential, parallel, and loop workflow patterns with seamless agent handoffs.
  • Extensive Provider Support: Compatible with 100+ LLMs including OpenAI, Anthropic, Gemini, and local models via Ollama.
  • Tool Integration: Native support for MCP (stdio, HTTP, WebSocket, SSE) and custom Python tools.
  • Advanced Agent Capabilities: Includes deep research, planning mode, self-reflection, and guardrails for input/output validation.
  • Deployment Options: Integrated dashboards for connecting agents to Telegram, Discord, Slack, and WhatsApp.
  • Persistence: Built-in support for 20+ databases (PostgreSQL, MongoDB, etc.) for session and memory management.