# Semantic search

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 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 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.

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.

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

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 Docker-based Python flashcard management server that uses OpenAI embeddings and SQLite for semantic search and storage functions.

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.

A lightning-fast, language-agnostic code analysis MCP server built on Rust, offering instant symbol lookup, reference tracking, and semantic code search. Designed for large codebases with performance as a priority.

BuildAutomata Memory is a persistent memory system based on the MCP protocol, providing semantic search and versioned memory storage across sessions for AI agents, supporting intelligent classification, timeline tracing, and multi-tool synchronization

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.

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.

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 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.

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.

markymark is a language server and AI agent tool for Markdown and structured data files, providing navigation, refactoring, search, and diagnostic functions, and supporting the LSP and MCP protocols.

Engram is an event - sourcing memory system designed for AI agents, adopting an architecture without an LLM write path, and achieving reliable semantic search memory storage through local vector embeddings and DuckDB.

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.

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

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

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.