"Guide to Building a Minecraft Protocol (MCP) Server" matching MCP servers:

Provides semantic search capabilities over the Plesk Extensions Guide documentation using Retrieval-Augmented Generation (RAG) and vector embeddings. It enables AI assistants to retrieve relevant technical information and answer natural language queries regarding Plesk extension development.

MCP server that ingests PDF documents into pgvector for semantic search and RAG pipelines. It handles extraction, chunking, local embeddings, and storage, enabling agents to make PDFs searchable via natural language.

Enables users to ingest PDF/DOCX/TXT/MD documents and ask natural language questions about them, using local embeddings and Groq-powered retrieval-augmented generation.

A conversational application server that integrates LLM capabilities via Ollama with vector memory context, supporting multiple users, sessions, automatic history summarization, and a plugin system for executing real actions.

A lightweight RAG system that provides an MCP server for searching and interacting with vector-based knowledge bases. It enables users to perform retrieval-augmented generation and search across Qdrant collections through a standardized interface.

A Model Context Protocol (MCP) server for Retrieval-Augmented Generation (RAG) operations. It provides tools for building and querying vector-based knowledge bases from document collections, enabling semantic search and document retrieval capabilities.

An MCP server that integrates with LangChain and ChromaDB to provide documentation search for AI libraries and vector database management.

Provides semantic search capabilities by connecting Claude Desktop to a Cloudflare Workers backend powered by Vectorize. It enables natural language querying of knowledge bases using vector similarity and edge-based embedding generation.

A server that enables vector and keyword search capabilities in Typesense databases through the Model Context Protocol, providing tools for collection management, document operations, and search functionality.

mcp-server-test

Enables AI agents to interact with Milvus vector databases and Zilliz Cloud through natural language, allowing users to create clusters, manage collections, insert vector data, and perform semantic searches directly from their AI assistants.

An MCP server that provides semantic memory on top of Qdrant vector search, with tools to store and retrieve information using embeddings.

A local-first knowledge base server that enables AI clients to store, retrieve, and manage documents using semantic search. Provides privacy-focused, offline-capable memory for AI assistants with tools for ingesting, querying, updating, and deleting knowledge.

Enables AI agents to autonomously create and manage topic-specific vector knowledge bases with end-to-end functionality including project creation, content ingestion from URLs, semantic search, and progress tracking. Provides a complete research workflow without exposing low-level APIs.

A Model Context Protocol (MCP) server for advanced code analysis and editing with semantic search capabilities, enabling AI assistants to perform complex code operations through a standardized interface.

A server that provides access to Baidu Cloud Vector Database functionality through the Model Context Protocol, enabling LLM applications to perform vector searches and database operations via natural language.

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

A Model Context Protocol server implementation that enables LLMs to interact with NebulaGraph database for graph exploration, supporting schema understanding, queries, and graph algorithms.

An MCP server for storing and retrieving memories using Qdrant vector search, acting as a semantic memory layer.

Enables persistent memory for AI systems by providing tools for episodic, semantic, and procedural data storage through a vector-and-graph-enhanced database. It allows models to maintain long-term continuity using similarity search, thematic clustering, and identity tracking.