# Semantic search

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.

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.

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.

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

CICADA is an MCP server that provides structured code indexing for AI code assistants. Through AST-level indexing, call site tracking, and semantic search, it provides efficient context compression for Elixir, Python, and Erlang code repositories, reducing token usage and improving the quality of code understanding.

DeepContext is an MCP server that provides symbol - aware semantic search capabilities for code assistants. By intelligently parsing code structure and semantic relationships, it can accurately locate relevant code snippets in large codebases and improve development efficiency.

Claude Context is an MCP plugin that provides in - depth context of the entire codebase for AI programming assistants through semantic code search. It supports multiple embedding models and vector databases to achieve efficient code retrieval.

Glider is a Roslyn-based MCP server that provides semantic analysis, intelligent refactoring, and architecture exploration capabilities for C# code in MCP clients (such as Claude Code).

Criterion is an AI - based Islamic knowledge assistant that provides authoritative guidance through the Quran and Hadith. It uses semantic search and real - time streaming response technology, is permanently free, and focuses on core doctrines.

DeepZotero is a tool that provides semantic search functionality for the Zotero literature library. It extracts text, tables, and images from PDFs, chunks, embeds, and stores them in ChromaDB. Finally, it provides 13 types of semantic search, Boolean search, table/image search, context expansion, citation graph query, index management, and cost - tracking tools to clients such as Claude Code through the MCP server.

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.

Context Lens is a local semantic search tool that can convert any content into a searchable knowledge base, enabling AI assistants to understand the meaning rather than just match keywords. It uses a built - in LanceDB vector database, supports local files, GitHub repositories, and URL content, does not require an API key or cloud service, and processes data completely locally.

A privacy - first document search server that runs entirely locally, providing semantic search functions for AI programming tools through the MCP protocol. No API keys or cloud services are required, and all data processing is completed on the user's computer.

The Vector Memory MCP Server provides long-term memory functions for AI assistants, supports saving and retrieving files or free-form notes, and enables natural language information queries through semantic search.

DMCP is a semantic tool discovery protocol that solves the problem of too many tools in MCP servers. It realizes on-demand query-driven tool discovery through vector search, significantly reducing token consumption and improving the accuracy of tool selection.

This is an MCP server designed for the Smart Connections plugin, providing read-only semantic search functionality for the Obsidian knowledge base, emphasizing security and lightweight implementation.

Memory MCP is an MCP server that provides persistent memory for AI assistants. Through a two - tier architecture of hot cache and cold storage, it enables zero - latency automatic injection of high - frequency knowledge and semantic search, allowing Claude to remember project contexts and reduce repeated explanations.

JitAPI is an MCP server that enables LLMs to interact with any API by dynamically discovering relevant endpoints in the OpenAPI specification. It uses semantic search and dependency graphs to find only the endpoints required for each task, supporting multi-API registration, LLM-driven workflow planning, and general execution.

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.

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).

The Smart Coding MCP server provides a semantic - based code search function for coding assistants through a local AI model, supporting multi - project management and progressive indexing.

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.

pg-aiguide is an AI-optimized PostgreSQL knowledge base that provides semantic search for official documentation, best practice skills, and extended ecosystem documentation for AI programming assistants, helping to generate higher-quality PostgreSQL code.

A lightweight Model Context Protocol (MCP) server that provides localized vector storage and database management to implement persistent memory and context management functions for AI assistants.

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.

An MCP server that provides relevant Ethereum Improvement Proposals (EIP) content for AI agents through semantic search, supporting Markdown document processing and vectorized retrieval.

A local vector database MCP server based on FAISS, providing document embedding, semantic search, and RAG functions, supporting multiple document formats and custom embedding models.

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, supporting text storage, semantic search, and integration of the FastEmbed embedding model.