# Semantic Search

Memento is a knowledge graph memory system based on SQLite, providing persistent memory functions, supporting full - text retrieval and semantic search, and realizing intelligent context retrieval through BGE - M3 embedding. It is suitable for technical and creative project management.

An MCP service for document retrieval based on vector search, providing relevant document context for AI assistants to enhance their answering ability

An MCP service for document retrieval based on vector search, providing relevant document context to enhance the response ability of AI assistants

The Vibe Coder MCP Server v4 is the final stable version, which introduces the Automatic Context Retrieval System (ACRS) and provides functions such as context memory, advanced caching, semantic search, and sequential thinking to enhance the capabilities of AI assistants.

An implementation of the MCP server based on txtai, providing semantic search, knowledge graph, and AI text processing functions.

The Mem0 MCP server is a model context protocol service that provides persistent memory capabilities for LLMs. It supports both cloud and local storage modes, enabling cross - session information storage and retrieval.

A YouTube MCP server project that provides video search, subtitle extraction, and semantic search functions, and supports integration with AI clients.

The Pippa MCP Memory Manager is an AI memory system designed for Cursor IDE, which implements cross - session persistent memory functions based on the MCP protocol.

The HubSpot MCP Server is middleware that connects an AI assistant to HubSpot CRM data, providing access to contact, company, and interaction data. It has vector storage and caching mechanisms to improve performance.

An MCP server implementation designed for the Claude desktop application, providing persistent memory functions for large language models, including a tiered memory architecture, multiple memory types, and semantic search features.

Semantic search MCP service based on the Qdrant vector database

An implementation of the MCP Server based on txtai, providing semantic search, knowledge graph, and AI text processing functions.

The Memvid MCP Server is an AI service interface based on video memory technology, supporting encoding content such as text and PDFs into video formats and providing semantic search and conversation functions.

Pixeltable's multi-modal model context protocol server set provides indexing and querying functions for audio, video, images, and documents

The OpenRouter Agents MCP Server is a research agent server based on the Model Context Protocol (MCP). It uses Claude 3.7 Sonnet as the planning agent to coordinate multiple OpenRouter models to decompose and execute complex research tasks, providing efficient and reliable AI research services.

The mem0 MCP Server is a middleware for project management, providing structured project memory storage, semantic search, and project information management functions, and supporting interaction with the MCP host application through the standard input - output protocol.

This project provides a set of tools for crawling website content and generating Markdown documents. It also implements semantic search for documents through the MCP server and supports integration with tools such as Cursor.

The Meilisearch Hybrid Search MCP service provides a hybrid search function that combines keywords and semantic vectors.

Aleph-10 is an MCP server that combines weather data services and vector memory storage, providing weather information query and semantic-based vector memory management functions, supporting multiple embedding options and metadata filtering.

A document semantic search service based on the Qdrant vector database, supporting URL and local file imports and providing natural language query functions.

MCP Apple Notes is a service based on the Model Context Protocol that can perform semantic search and Retrieval Augmented Generation (RAG) on Apple Notes, enabling AI assistants like Claude to reference users' notes in conversations.

The Jina AI MCP Server is a Model Context Protocol server that provides semantic search, image search, and cross-modal search functions, supporting seamless integration with Jina AI's neural search capabilities.

An implementation of the MCP server based on txtai, providing semantic search, knowledge graph, and AI text processing functions, supporting local knowledge base construction and standardized interface access.

MCP-Mem0 is a template implementation that provides long-term memory functions for AI agents, integrating the Model Context Protocol (MCP) server and Mem0, supporting memory storage, retrieval, and semantic search.

An MCP service for semantic search and memory management based on txtai, providing context memory capabilities for AI assistants

An MCP server that provides email processing functions, integrates MongoDB semantic search and SQLite for efficient storage, and supports Outlook email processing, vector embedding generation, and multi - email account management.

A local code indexing and semantic search tool

A Machine Control Protocol (MCP) server based on the Qdrant vector database for storing and retrieving text information, supporting semantic search and metadata storage.

A high-performance local RAG system based on Rust, integrated with Claude Desktop via the MCP protocol to achieve local processing, semantic search, and privacy protection of PDF documents.

An MCP server implementation designed for the Claude desktop application, providing persistent memory functions, including a tiered memory architecture, multiple memory types, and semantic search features.