# Semantic search

The MCP-RAG Server is an implementation based on the Model Context Protocol (MCP), aiming to provide real-time document access to AI assistants through semantic vector search, thereby generating context-aware responses based on the latest information.

An MCP server that connects AI assistants with HubSpot CRM data, providing access to contact, company, and interaction data. Built - in vector storage and caching mechanisms optimize performance.

An MCP service for semantic search of Apple Notes, supporting local embedding models, full-text search, and vector storage.

An MCP server based on Claude for document management and semantic search using Needle

A local server based on the MCP protocol that implements semantic search and RAG functions for Apple Notes, which can be called by AI assistants such as Claude.

NetContextServer is a tool that enhances AI programming assistants' understanding of .NET codebases. It provides functions such as in-depth code analysis, semantic search, and test coverage analysis through the Model Context Protocol (MCP).

A Python - based service application that provides functions for getting metadata from SharePoint and retrieving entities from the Neo4j knowledge graph through semantic similarity search.

A TypeScript-based MCP server that integrates with Mem0 to provide memory stream functions

The MCP Registry Server project provides a semantic search-based MCP server retrieval function, supporting quick installation through the Smithery tool and integration with Claude Desktop for use.

A knowledge graph server based on Neo4j, integrating AI models and the MCP protocol, supporting dynamic knowledge management and semantic search.

Kolada MCP Server is an intelligent middleware that connects large language models with the Swedish Kolada statistical database, providing functions such as semantic search, KPI analysis, and multi - year comparison, simplifying the query and interpretation of public - sector data.

This project provides a set of toolkits for crawling website content and generating Markdown documents. At the same time, it realizes the semantic search function of documents through the MCP server and supports integration with tools such as Cursor.

mc-mcp is an MCP server designed for the metacontract framework, providing support for smart contract development, including semantic document search, Foundry integration, and contract deployment.

A system integrating the Qdrant vector database and MCP server for storing and retrieving code snippets, supporting natural language search and semantic retrieval.

This project is an MCP server for Federal Open Market Committee (FOMC) statement analysis and retrieval, providing semantic search, trend analysis, and metadata access functions, and handling complex data processing processes through a simple tool interface.

This project is a semantic search tool based on Elasticsearch for semantic retrieval of Search Labs blog posts, including crawler configuration, index mapping update, and MCP server integration functions.

The mem0 MCP Server provides structured memory storage and semantic search services for project management

A semantic search MCP service based on the Qdrant vector database, supporting multi - collection retrieval and configurable result return

This project is a semantic search tool based on Elasticsearch for semantic retrieval of Search Labs blog posts, including crawler configuration, index mapping updates, and MCP server integration functions.

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

This is a knowledge base management tool based on the MCP server, which provides a list of knowledge base content and retrieval functions, and supports semantic search and automatic index updates.

A Machine Control Protocol (MCP) server based on the Qdrant vector database, supporting text storage, semantic search, and integration of the FastEmbed embedding model.