"RAG (Retrieval-Augmented Generation) system that can store papers and web pages" matching MCP servers:

Enables AI agents to search private GitHub Pages by authenticating in a dedicated browser and retrieving indexed sections from a local SQLite database, with support for multiple sites and languages.

A Model Context Protocol server that analyzes webpage design structures, providing detailed layout, navigation, content, form, image, and link information from a given URL.

Enables software and AI to work with accounting engagements through portable concepts such as trial balances, adjustments, working papers, and review notes, with declared adapter capabilities and validate-before-commit mutations.

A black-box flight recorder for RAG retrieval inside MCP agents. Logs what chunks the model saw, scores, sources, and rankings - so you can audit, replay, and diff retrieval runs after the fact.

MCP server that lets AI agents see and interact with terminal/CLI applications through virtual terminals and PNG screenshots.

Enables agents to search, analyze, and explore arXiv academic papers with advanced multi-field search, author lookup, category browsing, citation extraction, and bibliography export.

MCP server that adds vision capabilities to text-only AI models by sending images (local files, URLs, clipboard, screenshots) to a vision model and returning text descriptions.

MCP server for Facebook Pages organic analytics and management using Meta Graph API v25.0. Enables AI assistants to read page insights, posts, comments, and publish content via natural language.

Enables deployment of HTML content, folders, and full-stack projects to EdgeOne Pages to generate publicly accessible URLs. It utilizes EdgeOne Pages Functions and KV storage for high-performance edge delivery of web applications.

Enables AI agents to analyze whether they should send an email, evaluating passive aggression and regret probability with a recommendation heavily weighted toward no.

Fetches and renders tldr pages for commands, lists commands and platforms, and searches across page titles.

Enables post-hoc auditing of an agent's retrieval supply chain by recording digest-only provenance from source through chunk, transformation, context and decision, then reporting influence rankings with an honest unexplained residual, lineage traces, advisory source trust and retirement recommendations, and retrieval schema drift. It never performs retrieval, ranks documents at query time, or blocks decisions.

Minimal agent telemetry store with OTLP/HTTP ingestion to Postgres and MCP streamable-http tools for querying logs, traces, and metrics.

A secure, read-only MCP server for AI-powered system monitoring. It provides real-time OS metrics, config discovery, and safe log tailing to enable autonomous infrastructure audits without shell access risks.

Provides AI assistants with access to the Fake Store API for e-commerce prototyping and testing, enabling queries on products, carts, and users.

Enables interaction with MongoDB databases through CRUD operations, aggregation, and schema discovery, with automatic field validation and ObjectId conversion.

Generates beautiful App Store and Play Store screenshots by inserting app images into iPhone/iPad mockup frames with customizable text overlays and gradient backgrounds. Supports multiple device types and batch generation with both free and pro subscription tiers.

Enables creation and querying of knowledge bases using Google's Gemini API File Search feature, allowing AI applications to upload documents and retrieve information through RAG (Retrieval-Augmented Generation).

A comprehensive Model Context Protocol server that enables AI assistants to interact with and manage Windows systems, providing capabilities for file system operations, process management, system information retrieval, registry operations, service management, network diagnostics, and performance monitoring.

Provides local Retrieval-Augmented Generation (RAG) capabilities using Ollama for embeddings and ChromaDB for vector storage. It enables users to ingest and perform semantic searches across PDF, Markdown, and TXT documents within MCP-compatible clients.