#vector

A high-performance, pure Rust Model Context Protocol (MCP) server that provides persistent, semantic, and graph-based memory for AI agents. Unlike other memory solutions that require a complex stack (Python + Vector DB + Graph DB), this project is a single, self-contained executable. ✅ No External Database (SurrealDB is embedded) ✅ No Python Dependencies (Embedding models run via embedded ONNX runtime) ✅ No API Keys Required (All models run locally on CPU) ✅ Zero Setup (Just run one Docker container or binary) It combines: Vector Search (FastEmbed) for semantic similarity. Knowledge Graph (PetGraph) for entity relationships. Code Indexing for understanding your codebase. Hybrid Retrieval (Reciprocal Rank Fusion) for best results.

Vector Memory MCP Server A secure, vector-based memory server for Claude Desktop using sqlite-vec and sentence-transformers. This MCP server provides persistent semantic memory capabilities that enhance AI coding assistants by remembering and retrieving relevant coding experiences, solutions, and knowledge. ✨ Features 🔍 Semantic Search: Vector-based similarity search using 384-dimensional embeddings 💾 Persistent Storage: SQLite database with vector indexing via sqlite-vec 🏷️ Smart Organization: Categories and tags for better memory organization 🔒 Security First: Input validation, path sanitization, and resource limits ⚡ High Performance: Fast embedding generation with sentence-transformers 🧹 Auto-Cleanup: Intelligent memory management and cleanup tools 📊 Rich Statistics: Comprehensive memory database analytics 🔄 Automatic Deduplication: SHA-256 content hashing prevents storing duplicate memories 📈 Access Tracking: Monitors memory usage with access counts and timestamps for optimization 🧠 Smart Cleanup Algorithm: Prioritizes memory retention based on recency, access patterns, and importance

About Model Context Protocol server that packages GDAL-style geospatial workflows through Python-native libraries (Rasterio, GeoPandas, PyProj, etc.) to give AI agents catalog discovery, metadata intelligence, and raster/vector processing with built-in reasoning guidance and reference resources.

**Context Keeper** 基于LLM驱动的智能上下文记忆管理系统，专为AI Agent提供企业级记忆能力。 **核心创新**：独创"宽召回+精排序"架构，通过两阶段LLM协作实现多维度检索融合（向量+时间线+知识图谱），准确率从传统RAG的45%提升至**75%+**，召回率达**80%+**。 **技术亮点**：完整实现MCP协议（HTTP/WebSocket/SSE三种传输），四维统一上下文模型（Project/Topic/Conversation/Code），支持短期/长期记忆智能转换。 **性能表现**：10000+ QPS并发能力，P95延迟<500ms，用户/工作空间完全隔离。 **开源生态**：MIT许可，Go语言实现，深度集成Cursor/VSCode IDE。让AI助手真正拥有持续记忆能力，告别重复解释，开启智能协作新时代。

One MCP to Rule Them All. NCP consolidates over 50 scattered MCP tools into two unified tools (Find & Run). Your AI goes from confused to confident with 87% fewer tokens, zero tool confusion, and 5x faster responses. Perfect for teams drowning in MCP tool sprawl.

Transform your AI agents into Apple development experts! Apple RAG MCP gives you instant access to official Swift docs, design guidelines, and comprehensive Apple platform knowledge through cutting-edge RAG technology. With professional AI reranking and hybrid search across iOS, macOS, watchOS, tvOS, and visionOS documentation plus Apple Developer YouTube content, you'll get precise, contextual answers every time. Compatible with Cursor, Claude Desktop, and all MCP tools - start building smarter Apple apps today!

A Model Context Protocol (MCP) server that leverages a vector database to efficiently index and query the codebase.

Claude Context is an MCP plugin that adds semantic code search to Claude Code and other AI coding agents, giving them deep context from your entire codebase.

Spring AI Playground is a self-hosted web UI that simplifies AI experimentation and testing. It provides Java developers with an intuitive interface for working with large language models (LLMs), vector databases, prompt engineering, and Model Context Protocol (MCP) integrations. Built on Spring AI, it supports leading model providers and includes comprehensive tools for testing retrieval-augmented generation (RAG) workflows and MCP integrations. The goal is to make AI more accessible to developers, helping them quickly prototype Spring AI-based applications with enhanced contextual awareness and external tool capabilities.

An MCP server for Milvus that supports session connection management and accesses Milvus via the SSE interface.

Model–Context–Protocol (MCP) Server A modular, extensible Rust-based server providing short-term, long-term, and latent memory services, a chat endpoint backed by a BaseAgent + Sentience DSL, and seamless integration with ChromaDB and LLM services.

A powerful MCP server for generating, editing, and converting SVG images using AI, uses the best vector generation models

A Model Context Protocol (MCP) server for agentic retrieval and semantic search over unstructured and structured data using Milvus, a high-performance vector database. This server enables large language model (LLM) applications to efficiently index, store, and retrieve vector embeddings derived from diverse data sources—such as documents, images, metadata, or logs. By leveraging Milvus, the MCP server supports similarity search and contextual retrieval, enabling intelligent access to relevant information based on natural language queries. Designed for integration with MCP-compatible clients, this solution provides a scalable, low-latency foundation for building AI-powered applications with contextual awareness and retrieval-augmented generation (RAG) capabilities.

Self-hosted MCP Japanese text indexing & search—chunking+embeddings with BM25×vector rerank

API service to search vectorized Cursor IDE chat history using LanceDB and Ollama

API service to search vectorized Cursor IDE chat history using LanceDB and Ollama

Model Context Protocol Server for Mochow

MCP server for MariaDB

Servidor MCP que busca documentação mais atualizada de tools

🍀 🤖 Spring Boot AI - Evaluation Testing

A MCP (Model Context Protocol) server providing long-term memory for LLMs

A Model Context Protocol (MCP) server that enables AI assistants to interact with HubSpot CRM data, providing built-in vector storage and caching mechanisms help overcome HubSpot API limitations while improving response times.

OAuth2 Authorization Server with Spring Boot 3 and Java 24

A demo repository for testing the GitHub 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.

The Cursor10x MCP is a persistent multi-dimensional memory system for Cursor that enhances AI assistants with conversation context, project history, and code relationships across sessions.

Learn TypeScript chatting effortlessly with AI

MCP Server that integrates a knowledge graph and a vector database based on SQLite

This is a MCP server I built to interact with my hybrid graph rag db.

💬 MaxKB is an open-source AI assistant for enterprise. It seamlessly integrates RAG pipelines, supports robust workflows, and provides MCP tool-use capabilities.

YouTube MCP Server is an AI-powered solution designed to revolutionize your YouTube experience. It empowers users to search for YouTube videos, retrieve detailed transcripts, and perform semantic searches over video content—all without relying on the official API. By integrating with a vector database, this server streamlines content discovery.

A Model Context Protocol (MCP) server implementation for RAG

LanceDB MCP Server nodejs

🗂️ 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 database-level operations, making it easy to manage and query Turso databases directly from LLMs.

🗂️ 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 database-level operations, making it easy to manage and query Turso databases directly from LLMs.

[C#/AI] (LibraryAI/ConsoleAI) AI 知识库与数据处理程序

Vectorize MCP server for advanced retrieval, Private Deep Research, Anything-to-Markdown file extraction and text chunking.

An MCP server that provides tools for retrieving and processing documentation through vector search, both locally or hosted. Enabling AI assistants to augment their responses with relevant documentation context.

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 memories with semantic vector database search capabilities. You can use Claude and Cline AI as well.

MCP server providing semantic memory and persistent storage capabilities for Claude using ChromaDB and sentence transformers.

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 context.