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.

Acemcp is an MCP server for codebase indexing and semantic search, supporting automatic incremental indexing, multi-encoding file processing, .gitignore integration, and a Web management interface, helping developers quickly search for and understand code context.

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.

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.

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.

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.

The MCP Memory Service is a semantic memory storage system based on ChromaDB and sentence transformers, providing long - term memory and semantic search functions for Claude Desktop.

The MCP service of Suppr Super Literature provides document translation and Chinese semantic search for PubMed literature functions, supports multiple file formats and language mutual translation, and can be integrated into AI assistants such as Claude for use.

An MCP server that provides any AI model with the ability to intelligently search for Claude Agent Skills through vector embeddings and semantic similarity, enabling progressive skill discovery and cross-platform skill sharing.

PMAT is a zero-configuration AI code context generation tool that provides functions such as code quality analysis, technical debt grading, mutation testing, repository health scoring, and semantic search. It supports over 17 programming languages and can be integrated with AI assistants such as Claude Code through the MCP protocol.

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

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

A code preference management server based on the MCP protocol and mem0, providing storage, retrieval, and search functions for code snippets.

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

An MCP service for semantic search of Star Wars planets based on Couchbase

A remote ChromaDB server based on the Streamable HTTP MCP protocol, providing AI assistants such as Claude with the ability to remotely access the vector database, supporting cross - platform shared memory and semantic search.

The FHIR MCP Server is a medical data management server based on the FastMCP framework, providing a complete implementation of the Model Context Protocol (MCP) and supporting the interaction between LLM agents and FHIR-compatible backends. It provides standardized interfaces, supports comprehensive CRUD operations on FHIR resources, and implements intelligent document processing and semantic search through a series of tools.

An MCP memory server based on the Qdrant vector database, providing knowledge graph and semantic search capabilities.

An MCP server that provides semantic search and resource access for the Obsidian knowledge base

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.

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.

An MCP server based on Rust that provides in-depth code intelligent analysis, supporting functions such as symbol extraction, semantic search, security analysis, and supply chain security for 16 programming languages, with an emphasis on privacy and performance.

Claude local semantic code search tool that uses the EmbeddingGemma model to achieve fully offline intelligent multi - language code search. Integrates with Claude Code through the MCP protocol, protects privacy, and does not require an API key.

The WindTools MCP Server is a code assistant service based on ChromaDB and sentence transformers, providing document embedding and retrieval functions, and supporting codebase indexing and semantic search.

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

rag - mcp is an over - designed retrieval - augmented generation system that provides multiple text search modes (semantic search, question - answer search, style search) through a Python server. It uses PostgreSQL and pgvector to store text embedding vectors, supports interaction with AI agents, and has a complex but scalable architecture.

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).

Rememberizer's MCP server provides the ability to interact with document and knowledge management APIs for large language models

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.

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.

A high - performance MCP server for semantic code search, written in Rust, supporting hybrid search (BM25 + vector embedding), AST intelligent chunking, and over 60 programming languages.

A UK parliamentary data service project based on FastMCP, providing query and semantic search functions for data such as parliamentary members, constituencies, election results, government positions, parliamentary Q&A, and debate records, supporting access through MCP clients such as Claude.

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

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.

MCP-Memos is a memo tool based on the MCP protocol, designed specifically for developers. It supports quick recording and retrieval of text information without switching applications. It uses large language models to provide powerful fuzzy search capabilities, including semantic understanding, context awareness, and natural language query functions.

A document retrieval system based on MongoDB Atlas vector search and Voyage AI embedding technology, supporting semantic search and text matching, including document chunking, embedding generation, and storage functions.

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

An intelligent icon search and recommendation service based on Cloudflare Workers, achieving efficient icon discovery through multi-algorithm semantic matching

Zed's PDF semantic search extension, integrating an AI assistant to enhance document processing capabilities

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