by EvolutionAPI · MCP Server · ★ 556
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
Evo AI is an open-source platform for creating and managing AI agents, enabling integration with different AI models and services.
| Stars | 556 |
| Forks | 174 |
| Language | TypeScript |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 39.25/100 |
| Open Issues | 20 |
| Last Updated | 2025-06-02 |
| Created | 2025-05-13 |
| Platforms | mcp, node |
| Est. Tokens | ~7539k |
Looking for a evo-ai alternative? If you're comparing evo-ai with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
An introduction to the world of AI Agents
Flock is a workflow-based low-code platform for rapidly building chatbots, RAG, and coordinating multi-agent t
Model-agnostic plug-n-play LangChain/LangGraph agents powered entirely by MCP tools over HTTP/SSE.
ARGO is an open-source AI Agent platform that brings Local Manus to your desktop. With one-click model downloa
Turn topics, links, and files into AI-generated research notebooks — summarize, explore, and ask anything.
Open-source persistent memory for AI agent pipelines (LangGraph, CrewAI, AutoGen) and Claude. REST API + knowl
Explore other popular mcp server tools:
evo-ai is Evo AI is an open-source platform for creating and managing AI agents, enabling integration with different AI models and services.. It is categorized as a MCP Server with 556 GitHub stars.
evo-ai is primarily written in TypeScript. It covers topics such as a2a-protocol, adk, agent.
You can find installation instructions and usage details in the evo-ai GitHub repository at github.com/EvolutionAPI/evo-ai. The project has 556 stars and 174 forks, indicating an active community.
evo-ai is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to evo-ai on Agent Skills Hub include oreilly-ai-agents, flock, DeepMCPAgent. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.