vinagent — MCP Server by datascienceworld-kan

by datascienceworld-kan · MCP Server · ★ 73

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About vinagent

Introduction is a lightweight and flexible library designed for building smart agent assistants across various industries. Whether you're creating an AI-powered customer service bot, a data analysis assistant, or a domain-specific automation agent, vinagent provides a simple yet powerful foundation. With its modular tool system, you can easily extend your agent's capabilities by integrating a wide range of tools. Each tool is self-contained, well-documented, and can be registered dynamically—making it effortless to scale and adapt your agent to new tasks or environments. ![](asset/agentsystemdesign

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Quick Facts

Stars73
Forks11
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score64.1002555408617/100
Open Issues1
Last Updated2026-03-25
Created2025-05-18
Platformsmcp, python
Est. Tokens~1464k

vinagent alternative? Top 6 similar tools

Looking for a vinagent alternative? If you're comparing vinagent 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.

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Frequently Asked Questions

What is vinagent?

vinagent is Vinagent is a comprehensive Agentic AI library that helps integrate tools, memory, workflows, and observability.. It is categorized as a MCP Server with 73 GitHub stars.

What programming language is vinagent written in?

vinagent is primarily written in Python. It covers topics such as agent, agentic-ai, agentic-workflow.

How do I install or use vinagent?

You can find installation instructions and usage details in the vinagent GitHub repository at github.com/datascienceworld-kan/vinagent. The project has 73 stars and 11 forks, indicating an active community.

What license does vinagent use?

vinagent is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to vinagent?

The top alternatives to vinagent on Agent Skills Hub include DeepWideResearch, Agentic-AI-Systems, oreilly-ai-agents. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

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