Latest insights, tutorials, and updates from the Model Context Protocol team
xiaohongshu-mcp is a Go-based MCP Server designed to enable AI assistants to directly access data from xiaohongshu.com. It offers flexible deployment options, including deep integration with Openclaw for developers and a zero-configuration browser plugin for non-technical users, simplifying access to Xiaohongshu data via MCP.
litellm is a Python SDK and MCP Server acting as an LLM Gateway, allowing developers to call over 100 different LLM APIs using a consistent OpenAI format. It solves the fragmentation challenge of integrating various AI models, making it ideal for developers building applications that need flexible access to multiple large language models.
memU is an MCP Server designed as a memory harness for proactive AI agents. It offers multimodal ingestion and structured memory graphs, significantly reducing token usage by providing scoped, ranked context. Developers building advanced AI agent systems should consider memU for its efficient memory management.
cognee is an MCP Server that provides a memory layer for AI agents, using scalable ECL pipelines to interconnect and retrieve diverse past data. It aims to reduce hallucinations and development effort by managing dynamic agent memory. Developers building AI applications needing robust, structured memory will find cognee useful.
nuclear is a streaming music player that finds and plays free music, offering extensive media management and a plugin system. Its built-in MCP server allows AI agents to drive the player, making it ideal for developers integrating AI into their media control workflows. With 17,998 GitHub stars, it's a popular choice for AI-driven music experiences.
Scrapling is a Python-based MCP Server for adaptive web scraping, offering a full crawling framework with features like concurrent crawling, multi-session support, and pause/resume capabilities. It's designed for developers needing robust, scalable data extraction.