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CodeRabbitTracking and experimenting with agent communication protocols. Currently focused on MCP (Model Context Protocol) with hands-on examples and insights.
"Automated summary for AI agents and search engines."
Tracking and experimenting with agent communication protocols. Currently focused on MCP (Model Context Protocol) with hands-on examples and insights.
{"id":"95f85f55-e19f-4f5f-9080-9d9f1dde63fe","title":"Agentic Ai Protocols","description":"This repository provides implementations and examples of various agentic AI protocols, showcasing different approaches to autonomous agent design and interaction. It allows developers to explore patterns for goal-driven task execution, self-correction, and tool utilization within AI systems, serving as a valuable resource for understanding advanced agent architectures.","dateModified":"2026-04-03","difficulty":"advanced","tags":["ai-protocols","agent-frameworks","autonomous-agents","python","research-code"],"tokenImpact":"Lightweight — typically under 500 tokens per call, low lockout risk.","schemaDescription":"A Python-based collection of implementations demonstrating diverse agentic AI protocols, including patterns for autonomous task execution, self-reflection, and external tool integration, aiding in the development of sophisticated AI agents.","author":"DevHammad0","authorGithub":"https://github.com/DevHammad0/agentic-ai-protocols","license":"Unknown","transport":"Unknown","language":"Python","useCases":["Studying and experimenting with different agentic AI architectures.","Prototyping new autonomous agent behaviors.","Understanding how agents can leverage tools and self-correction.","Developing novel AI agent research projects."],"exampleCommand":"git clone https://github.com/DevHammad0/agentic-ai-protocols && cd agentic-ai-protocols && pip install -r requirements.txt","mcpConfig":"NONE","compatibility":["Google Antigravity IDE"],"copyButtonText":"Copy mcp_config.json","artifactsProduced":["Agent code examples","Protocol implementations","Experiment results","Agent task plans"],"faq":[{"question":"What can you do with Agentic Ai Protocols?","answer":"This repository offers code examples and implementations of various agentic AI protocols, allowing developers to study, experiment with, and build autonomous agents that feature goal-driven task execution, self-correction mechanisms, and advanced tool utilization for complex problem-solving."},{"question":"Which AI assistants and IDEs are compatible with Agentic Ai Protocols?","answer":"Agentic Ai Protocols is a collection of reference implementations and does not directly integrate as an MCP server. However, the agent architectures and concepts demonstrated can be adapted and integrated into agent development frameworks, making them compatible with AI assistants and IDEs like Google Antigravity IDE that support custom agent deployments."},{"question":"How do I install and configure Agentic Ai Protocols?","answer":"To explore Agentic Ai Protocols, clone the repository using `git clone https://github.com/DevHammad0/agentic-ai-protocols` and navigate into the directory. Install dependencies with `pip install -r requirements.txt`. Configuration involves running and modifying the provided Python scripts to experiment with different agent behaviors and protocols."}]}🚀 The fast, Pythonic way to build MCP servers and clients.
MCP web search using perplexity without any API KEYS
一个基于 MCP (Model Context Protocol) 的邮件服务，支持 LLM 发送带附件的电子邮件及在指定目录中搜索文件。提供安全的 SMTP 传输、多收件人支持和附件模式匹配搜索功能，适用于 Gmail、Outlook、Yahoo、QQ 邮箱和网易 126 邮箱等主流邮箱服务。
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