"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
An MCP server demo for retrieving Market information
A suite of AI agents and tools built on Model Context Protocol (MCP) for standardized, context-aware AI systems.
🤖 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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