关键词 "Vector icons" 的搜索结果， 共 13 条, 只显示前 480 条
An intelligent code memory system that leverages vector embeddings, structured databases, and knowledge graphs to store, retrieve, and analyze code patterns with semantic search capabilities, quality
MCP server providing a knowledge graph implementation with semantic search capabilities powered by Qdrant vector database
A Model Context Protocol (MCP) server implementation that provides vector database capabilities through Chroma.
Model Context Protocol (MCP) server implementation for semantic vector search and memory management using TxtAI. This server provides a robust API for storing, retrieving, and managing text-based memo
An MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation contex
🗂️ A Model Context Protocol (MCP) server that provides integration with Turso databases for LLMs. This server implements a two-level authentication system to handle both organization-level and databas
The Milvus MCP server enables AI applications to interact with Milvus vector databases using natural language commands. It allows AI models to perform vector searches, manage collections, and retrieve
MCP Server that integrates a knowledge graph and a vector database based on SQLite
AWS Aurora Postgres with Pgvector Extension MCP Server.
A powerful knowledge management system that forges wisdom from experiences, insights, and best practices. Built with Qdrant vector database for efficient knowledge storage and retrieval.
A magical design tool for Figma powered by AI. Wave Your Magic Wand. Design with the power of AI to do everything from copywriting to generating unique icons ...
BnbIcons是AI驱动的图标生成工具，能创建类似Airbnb风格的等轴测图标。用户只需输入文字描述或上传参考图片，AI能生成符合要求的图标。提供464+个预制图标，涵盖多种类别和风格，可快速找到所需图标。用户可以批量创建图标，输入一系列类别，可生成整套匹配的图标，节省设计时间。 BnbIcons的主要功能 AI辅助图标生成：通过AI技术，根据用户输入的文本描述或上传的参考图片，快速
OmniGen2 是北京智源人工智能研究院推出的开源多模态生成模型。能根据文本提示生成高质量图像，支持指令引导的图像编辑，比如修改背景或人物特征等。OmniGen2 采用双组件架构，结合视觉语言模型（VLM）和扩散模型，实现对多种生成任务的统一处理。优势在于开源免费、高性能以及强大的上下文生成能力，适用于商业、创意设计和研究开发等场景。 OmniGen2的项目地址 项目官网：https:/
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