Evo AI - AI Agent Frameworks Tool

Overview

Evo AI is an open-source agents platform for building, running, and observing autonomous AI agents and agent-driven workflows. According to the GitHub repository (https://github.com/EvolutionAPI/evo-ai), the project provides multiple agent types — including sequential, parallel, and workflow agents — together with a bundled web UI and backend to orchestrate agent behavior. The platform emphasizes agent-to-agent (A2A) communication via a defined protocol and offers tracing/instrumentation through Langfuse for observability. Evo AI is positioned as a developer-oriented framework for composing multi-agent systems and long-running pipelines. The included UI gives teams a visual way to monitor agents, view traces, and inspect execution traces; the backend exposes APIs and runtime components to integrate agents into applications. Because the project is hosted on GitHub and described as open-source, teams can self-host, extend agent types, and adapt the A2A protocol to their needs. For full installation and configuration details, the repository README and docs should be consulted directly.

Installation

Install via docker:

git clone https://github.com/EvolutionAPI/evo-ai.git

cd evo-ai

docker compose up --build

Key Features

• Sequential agents for step-by-step task execution and deterministic pipelines.
• Parallel agents to execute tasks concurrently across independent workers.
• Workflow agents that model multi-step pipelines and conditional branching.
• Integrated web UI and backend for orchestration, monitoring, and control.
• A2A protocol enabling explicit agent-to-agent messaging and coordination.
• Tracing integration with Langfuse for end-to-end observability and debugging.

Community

Evo AI is maintained as an open-source project on GitHub (see repository link). The project accepts issues and pull requests for bug fixes, feature requests, and integrations. Community engagement typically happens via the repository's issue tracker and PRs; contributors should consult the README and contributing guidelines in the repo for setup, tests, and coding standards. No commercial pricing information is provided in the repository; the project appears intended for self-hosting and community contribution.

Key Information

• Category: Agent Frameworks
• Type: AI Agent Frameworks Tool