# Semantic Search

This is a PostgreSQL semantic search server based on the Model Context Protocol (MCP) standard. It enables AI assistants to understand the semantic structure of the database and execute natural language queries through vector embedding technology.

Slunk is a real-time Slack search tool for macOS, providing intelligent chat analysis through local semantic search and MCP service integration

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.

This project builds an AI system based on Nasdanika capabilities, focusing on operating on resource collections (interconnected models). It describes model elements and their relationships from multiple angles through the 'narrator' processor, and uses embeddings and vector storage to implement semantic search and RAG (Retrieval - Augmented Generation). It also supports the chat completion functions of OpenAI and Ollama.

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.

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.

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

An MCP server that provides functions for YouTube video search, subtitle extraction, and semantic search

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.

A RAG service based on the Qdrant vector database and Ollama/OpenAI embedding, providing document semantic search and management functions.

Hanzo MCP is an AI service platform based on the Model Context Protocol, providing capabilities for code analysis, modification, project management, and integration with multiple development tools.

A memory server implementing the Model Context Protocol (MCP), providing persistent memory storage and retrieval functions based on a knowledge graph for large language models.

MEMEX is a knowledge management server based on the MCP protocol, used to manage technical guides and AI context, providing functions for creation, search, update, and deletion, and supporting semantic search and integration with Claude AI

OneMCP is a universal MCP protocol aggregator that uniformly manages tools from multiple external MCP servers through a meta-tool architecture. It uses progressive discovery and semantic search technologies to significantly reduce token consumption of LLMs and improve tool discovery efficiency.

An MCP server for storing, searching, and managing code snippets, supporting semantic search and keyword matching, without a database, and using JSON for storage.

A remote ChromaDB server based on the Streamable HTTP MCP protocol, providing AI assistants such as Claude with the ability to remotely access the vector database, supporting cross - platform shared memory and 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 Obsidian plugin that provides local MCP server capabilities, enabling external applications to interact with the Obsidian library through standardized interfaces, including file operations, semantic search, etc.

An MCP server that provides email processing capabilities, integrating MongoDB semantic search and SQLite efficient storage

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 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.

GraphRAG MCP is a hybrid retrieval system that combines the Neo4j graph database and the Qdrant vector database, providing document retrieval services that combine semantics and graph relationships for large language models.

An LLM long-term memory storage system based on the MCP standard, supporting semantic search and multi-type memory management

An experimental local code indexing service based on Python that uses ChromaDB for storage and provides semantic search functionality, serving tools such as Cursor through the MCP protocol.

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.

An MCP server that enhances the functionality of the Qdrant vector database, providing functions such as collection management, document addition, and semantic search.

A hybrid retrieval and navigation tool for RimWorld source code and XML definitions, combining lexical, semantic, and graph structures, supporting AI assistant calls

The SourceSync.ai MCP Server is a standardized implementation of a knowledge management platform interface that allows AI models to interact with the SourceSync.ai platform through the MCP protocol.

An MCP server for expanding the context window/memory of AI agents, supporting storage, retrieval, and management of memories, including semantic search functionality.