"Semantic search, RAG, and memory systems" matching MCP servers:

Enables agentic workflows to execute allow-listed side effects with automatic reverse-order compensation on failure, durable SQLite journaling, and idempotent rollback via MCP tools.

Enables comprehensive Google Meet and Calendar management through Google Calendar API v3 and Google Meet API v2, supporting calendar event creation with Meet links, space management, transcription, recording, attendance tracking, and meeting moderation controls.

MCP server for step-by-step mathematical reasoning and planning, enabling AI agents to execute calculations and perform GUI actions like opening PowerPoint.

An MCP server that enables users to search for movie and TV show resources across multiple sources and validate video link playability. It supports both STDIO and SSE transport modes for seamless integration with AI applications.

Enables AI assistants to search YouTube videos with rich metadata including titles, channels, view counts, and duration. Supports multi-language search and is designed for remote deployment on the Dedalus platform.

A Python MCP server that allows programmatic interaction to find torrents programmatically on ThePirateBay, Nyaa and YggTorrent.

MCP server for searching images with Google

A Python MCP server that allows programmatic interaction to find torrents programmatically on YggTorrent and La Cale.

Model Context Protocol server for the GlobKurier API. Enables AI assistants (Claude, Cursor, Cline and others) to track shipments, search shipping products and generate purchase links.

A simple Model Context Protocol (MCP) server that provides date and time functionality in any timezone, along with user profiles and personalized greeting resources.

Enables synchronization and management of FoundryVTT journal entries within a Notion Story Bible, including media export and conflict resolution tools. It provides a Model Context Protocol interface for LLMs to preview, apply, and monitor data mirroring between tabletop RPG platforms and digital databases.

A Python-based Model Context Protocol server that allows AI assistants like Claude to access and query your movie and TV show collection via Radarr and Sonarr APIs.

Enables AI assistants to interact with Inflow Inventory API for managing ingredients/products and inventory operations. Supports product creation, updates, search, and stock adjustments through natural language commands.

lets you interact with your meeting data (to list, ask, summarize, extract - virtually anything about your meeting) through Claude’s desktop client across Zoom, Google Meet and MS Teams via tl;dv.

Enables users to search Airbnb listings with advanced filtering options and retrieve detailed property information through an MCP server interface.

Enables AI assistants to interact directly with Roblox Studio to explore project hierarchies, edit scripts, and perform bulk object manipulations through over 37 specialized tools. This enhanced fork features long polling for near-instant responses and improved support for script editing and attribute management.

Enables searching for AI/ML internships and entry-level positions across multiple job sites including LinkedIn, Indeed, Glassdoor, ZipRecruiter, and Monster. Automatically filters for Python proficiency and relevant AI/ML skills while providing structured job data with application URLs and detailed requirements.

Enables AI models to search the web for current information before generating responses, with features for conditional searching, geographic customization, and automatic citations.

A production-ready foundation template for building Model Context Protocol (MCP) servers with FastAPI, featuring modular tools, comprehensive testing, and OpenShift deployment configurations. Includes automated transformation scripts to create custom domain-specific MCP servers.

Enables simulation and analysis of M/M/1 and M/M/c queuing systems using SimPy, with tools for parameter validation, theoretical metric calculation, simulation execution, and comparison of separate vs pooled queue strategies.