关键词 "reference materials" 的搜索结果, 共 15 条, 只显示前 480 条
MCP Server for Thai plate prophecy. This project is designed to help customers predict or "prophecy" potential license plate numbers. By leveraging algorithms and user input, it provides insights and
eShopLite is a set of reference .NET applications implementing an eCommerce site with features like Semantic Search, MCP, Reasoning models and more.
🔥🖥️ MCP Memory is a MCP Server that gives MCP Clients (Cursor, Claude, Windsurf and more) the ability to remember information about users (preferences, behaviors) across conversations.
Branch-Thinking MCP Tool A TypeScript-powered MCP server for managing parallel branches of thought, semantic cross-references, and persistent tasks. Features dynamic scoring, AI-generated insights, ba
The VanMoof MCP Server implements the MCP specification to create a seamless connection between AI agents and key VanMoof services like VanMoof customer data, including bike details, VanMoof rider cit
MCP server for MusicXML references.
🔍 This project implements a Model Context Protocol (MCP) server for interacting with the Semantic Scholar API. It provides tools for searching papers, retrieving paper and author details, and fetching
Generate images from text using advanced AI models. Learn more about jigsawstack's image generation API here: https://jigsawstack.com/docs/api-reference/ai/image-generation You can get your jigsawstac
Windows MCP server setup differs from Mac by requiring absolute file paths and explicit node.exe references instead of npx commands. The installation requires verifying npm and installing packages glo
🔒 Reference MCP servers that demo how authentication works with the current Model Context Protocol spec.
An mcp server that you can use to store and retrieve ideas, prompt templates, personal preferences to use with you favourite AI tool that supports the modelcontextprovider protocol.
ContextGem:轻松从文档中提取 LLM ContextGem 是一个免费的开源 LLM 框架,它可以让您以最少的代码更轻松地从文档中提取结构化数据和见解。 💎 为什么选择 Contex
MAGREF(Masked Guidance for Any‑Reference Video Generation)是字节跳动推出的多主体视频生成框架。MAGREF仅需一张参考图像和文本提示,能生成高质量、主体一致的视频,支持单人、多人及人物与物体、背景的复杂交互场景。基于区域感知动态掩码和像素级通道拼接机制,MAGREF能精准复刻身份特征,保持视频中人物、物体和背景的协调性与一致性,适用内容创作
只显示前20页数据,更多请搜索
Showing 193 to 207 of 207 results