# Semantic Search

The SourceSync.ai MCP Server is a standardized implementation of a knowledge management platform interface that allows AI models to interact with the SourceSync.ai platform through the MCP protocol.

This is a PostgreSQL semantic search server based on the Model Context Protocol (MCP) standard. It enables AI assistants to understand the semantic structure of the database and execute natural language queries through vector embedding technology.

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

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

An implementation of the MCP server based on txtai, providing semantic search, knowledge graph, and AI text processing functions.

An MCP server that provides file semantic search functionality, enabling intelligent retrieval of document contents through vector embedding

The Jina AI MCP server is a Model Context Protocol service that provides semantic search, image search, and cross-modal search functions, supporting seamless integration with Jina AI's neural search capabilities.

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

A scalable OpenAPI endpoint discovery and API request tool that quickly locates API endpoints and executes requests through semantic search, especially suitable for handling large OpenAPI documents.

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.

This project builds an AI system based on Nasdanika capabilities, focusing on operating on resource collections (interconnected models). It describes model elements and their relationships from multiple angles through the 'narrator' processor, and uses embeddings and vector storage to implement semantic search and RAG (Retrieval - Augmented Generation). It also supports the chat completion functions of OpenAI and Ollama.

Pixeltable's multi-modal model context protocol server set provides indexing and querying functions for audio, video, images, and documents

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

The Onyx MCP Server is a protocol server that connects MCP clients to the Onyx knowledge base, providing semantic search and intelligent chat functions.

Aleph-10 is an MCP server that combines weather data services and vector memory storage, providing weather information query and semantic-based vector memory management functions, supporting multiple embedding options and metadata filtering.

An MCP server that provides functions for YouTube video search, subtitle extraction, and semantic search

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.

An MCP service for semantic search and memory management based on txtai, providing context memory capabilities for AI assistants

An MCP server implementation designed for the Claude desktop application, providing persistent memory functions, including a tiered memory architecture, multiple memory types, and semantic search features.

Hanzo MCP is an AI service platform based on the Model Context Protocol, providing capabilities for code analysis, modification, project management, and integration with multiple development tools.

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 code navigation MCP server based on semantic search, achieving efficient code retrieval through AI embedding and AST parsing, and reducing token consumption

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.

FastApply MCP Server is an enterprise-level code intelligence platform that provides comprehensive code analysis, search, and refactoring capabilities through local AI models, AST semantic search, security scanning, and intelligent pattern recognition. It supports multi-language development and large codebase processing.

A hybrid retrieval and navigation tool for RimWorld source code and XML definitions, combining lexical, semantic, and graph structures, supporting AI assistant calls

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

An MCP service for document retrieval based on vector search, providing relevant document context to enhance the response ability of AI assistants

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.

The Vibe Coder MCP Server v4 is the final stable version, which introduces the Automatic Context Retrieval System (ACRS) and provides functions such as context memory, advanced caching, semantic search, and sequential thinking to enhance the capabilities of AI assistants.

An implementation of the MCP Server based on txtai, providing semantic search, knowledge graph, and AI text processing functions.