# 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.

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

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.

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.

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.

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

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.

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.

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.

A high-performance MCP server that provides persistent multimodal context storage for LLM agents, supports thread isolation, metadata filtering, full-text search, and semantic search, and is compatible with SQLite and PostgreSQL backends.

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.

This is an MCP server for Microsoft Dynamics 365 Finance & Operations development. It accesses over 50,000 F&O standard components through semantic search, enabling AI assistants to find relevant implementation patterns and read local source code during development.

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 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.

CodeFlow is an intelligent code analysis tool that generates detailed call graphs by parsing the abstract syntax tree of the code and provides semantic search functionality. It includes two interfaces, a CLI tool and an MCP server, aiming to help developers understand complex codebases with minimal cognitive burden.

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.

This is an MCP service that provides a free public API directory, supports semantic search and detailed API information queries, and is built on a public API dataset.

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.

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.

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.

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

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.

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.

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.

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

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

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.