"Streamable HTTP" MCP server deployed on AWS Lambda and amazon API Gateway. The server provides a tool for Amazon Bedrock spend analysis.
The Model Context Protocol is an open standard that enables developers to build secure, two-way connections between their data sources and AI-powered tools. The architecture is straightforward: developers can either expose their data through MCP servers or build AI applications (MCP clients) that connect to these servers.
Production-ready Model Context Protocol (MCP) servers in Python, Go, and Rust for VS Code integration. Enables AI systems to interact with tools via standardized interfaces.
The llm_to_mcp_integration_engine is a communication layer designed to enhance the reliability of interactions between LLMs and tools (like MCP servers or functions).
Modern web interface for Knowledge RAG System with MCP integration
A suite of AI agents and tools built on Model Context Protocol (MCP) for standardized, context-aware AI systems.
An MCP server demo for retrieving Market information
🤖 Enterprise-grade AI agent framework with Tools4AI integration, web automation, and MCP protocol support. Features intelligent screenshot capture, meme generation, LinkedIn search, and real-time AI interactions. Built with Spring Boot, PostgreSQL, Redis, and Playwright automation. Perfect demonstration of modern Java/AI integration patterns
🔗 GitHub MCP Tool | 基于MCP协议的GitHub工具，为Cursor编辑器提供AI操作GitHub能力 | AI-powered GitHub operations for Cursor Editor through MCP protocol
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