# Semantic Search

The Jina AI MCP server is a Model Context Protocol service 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.

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.

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.

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.

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.

Cursor10x is an AI - powered development memory system that provides persistent context memory capabilities for the Cursor editor. It integrates four memory types: short - term, long - term, episodic, and semantic, to achieve intelligent code assistance.

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

Fabric Atelier is a high-performance MCP server built on Rust and Apache Arrow, exposing over 200 Fabric AI patterns as executable tools to AI assistants, supporting semantic search and quick pattern discovery.

Continuo is a persistent memory system that provides semantic search and hierarchical compression functions for the development environment, enabling cross - session knowledge storage and retrieval through a vector database and the MCP protocol.

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 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.

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.

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

An MCP server that provides file semantic search functionality, enabling intelligent retrieval of document contents through vector embedding

A scalable OpenAPI endpoint discovery and API request tool that quickly locates API endpoints and executes requests through semantic search, especially suitable for handling large OpenAPI documents.

A lightweight MCP server project for loading local PDF files, extracting and chunking content, building semantic search indexes, and sending relevant paragraphs to Claude Desktop for document-based Q&A.

MCPverse is a semantic - search - based discovery engine for GitHub MCP servers, implementing natural - language search functionality using OpenAI embeddings and OpenSearch.

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

A local code indexing and semantic search tool

A semantic search service for retrieving MCP servers

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.

This project provides code examples for developing and running an MCP server on Oracle OCI, including Python development, AI agent integration, semantic search, SelectAI integration, and connection with AI assistants such as ChatGPT, to help build enterprise - level AI applications.

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

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.