"Setting up services on a Linux virtual machine" matching MCP servers:

Enables AI-assisted chiller troubleshooting by exposing MCP tools to retrieve operational data, alarms, telemetry, and service history from MongoDB Atlas, plus vector and hybrid search over knowledge bases.

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.

Privacy-first local document search using semantic search. Runs entirely on your machine with no cloud services, supporting PDF, DOCX, TXT, and Markdown files.

Provides AI assistants with long-term semantic memory capabilities through local vector-based storage. Enables storing, recalling, and managing information across sessions with complete privacy using ChromaDB, with no data ever leaving your machine.

Enables LLM hosts to retrieve live, relevant documentation excerpts from official library docs sites via a search-and-RAG tool, avoiding reliance on training data.

RAG Vault lets your AI coding assistant search your private documents locally. Everything runs on your machine and your data stays private.

Model Context Protocol server for RosalindDB, enabling AI clients to create datasets, ingest vectors, run similarity queries, and check usage on a cost-optimized vector search database.

Enables making REST API calls to Teradata cloud services including Elastic Compute, Vector Store, OMS, and QueryGrid. Supports custom authentication, Socks5 proxy, and multipart file uploads.

Semantic memory MCP server that gives AI agents a self-writing, priority-based memory with local semantic search and automatic contradiction handling. It persists across sessions and projects, entirely on your machine.

An MCP server for OpenServerless that exposes action tools for creating, invoking, and managing API endpoints with integrated services like S3, PostgreSQL, Redis, and Milvus.

Headless geometric memory engine for AI agents — no Vector DB, no cloud, no API key. Store and retrieve by meaning using native Vector Symbolic Architecture (NVSA) math over O_DIRECT NVMe mapping. Runs entirely on your machine via MCP.

Provides persistent memory management for AI agents with 14 tools, including semantic search, context synthesis, auto-context middleware, and write-back actions to external services like Slack.

Enables Claude to interact with core AWS services like S3, EC2, RDS, and CloudWatch, along with a generic SDK wrapper for any AWS operation. It also supports cost monitoring and optional vector store capabilities for document ingestion and search.

A service discovery and proxy for MCP servers that enables registration, discovery, and execution of tools on remote MCP servers. Uses vector-based similarity search through Alibaba Cloud services to intelligently route requests to appropriate MCP services.

A Model Context Protocol server that enables semantic search capabilities by providing tools to manage Qdrant vector database collections, process and embed documents using various embedding services, and perform semantic searches across vector embeddings.

A Model Context Protocol server that enables users to perform third-party enrichment lookups for security observables (IP addresses, domains, URLs, emails) through services like VirusTotal, Shodan, and others.

Provides a private, on-device memory with semantic search for MCP clients, enabling encrypted storage and recall of context facts without external API calls.

Provides zero-knowledge, local-first persistent memory for AI assistants with on-device embeddings, cross-platform capture, and zero-RTT semantic recall.

An interface for managing and querying MariaDB databases that supports standard SQL operations alongside advanced vector and embedding-based search capabilities. It enables AI assistants to seamlessly integrate relational and vector data workflows through a standardized protocol.

Enables MCP clients to remember user information, preferences, and behaviors across conversations using vector search technology. Built on Cloudflare infrastructure with persistent storage and semantic similarity matching.