"A server or tool using RAG for documentation scraping, storage, and retrieval with SSE support" matching MCP servers:

Enables AI applications to interact with decentralized storage through a standardized Model Context Protocol interface, allowing file uploads, retrievals, and identity management.

Provides live wait times and office details for all 60 Oregon DMV field offices by scraping the ODOT website, with no authentication required.

Enables deterministic auditing of RAG retrieval faithfulness and hallucination scores, providing structured JSON output for AI agents and MCP-compliant clients.

Enables AI assistants to fetch public web pages as readable text or HTML, with caching, live refresh, and parallel job handling.

Enables searching and retrieving Italian regulated company disclosures from 1INFO, with same-day-fresh document indexing and filtering by issuer, category, and publication date.

An MCP server that provides AI assistants with access to Vonage API documentation, code snippets, tutorials, and troubleshooting resources.

Implements a Model Context Protocol server using Server-Sent Events for real-time communication with OAuth 2.1 integration via Ory Network, enabling secure AI model communication with authentication and client management.

Bridges AI agents with watsonx.data document libraries, enabling natural language queries and intelligent retrieval from document libraries.

Give your AI agents instant access to Keboola API documentation. Search endpoints, get parameter details, and generate curl examples—all through MCP tools.

Exposes a RAG document-search API as MCP tools (rag_health, rag_ingest, rag_query), enabling agents to index and search markdown documents with cited results through natural language.

Enables async-first working practices by providing tools to draft decision docs, convert meetings to async artifacts, score status updates, and triage sync vs async tasks. It also offers reference tools for the Open and Async book's principles and coaching prompts.

Enables management of Zadara VPSA Storage Arrays and Object Storage endpoints, including volume operations, snapshot creation, and bucket management. It allows users to interact with storage resources and retrieve performance metrics using natural language or custom API requests.

A Model Context Protocol server for indexing and searching local document collections with hybrid BM25+vector search, optimized for Korean and English, supporting DOCX, PDF, audio, and more.

Implementation of an MCP server for the RAG Web Browser Actor. This Actor serves as a web browser for large language models (LLMs) and RAG pipelines, similar to a web search in ChatGPT.

Enables local knowledge base management with retrieval-augmented generation (RAG), providing semantic search, document reading, listing, and Q&A via MCP tools and REST endpoints, all running locally without cloud dependencies.

A Model Context Protocol server that provides AI assistants access to AWS CloudWatch Logs, enabling browsing, searching, summarizing, and correlating logs across multiple AWS services.

This read-only MCP Server allows you to connect to Azure Data Lake Storage data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

Minimal local RAG stack with an MCP server that provides document search for any agent.

A hosted multimodal RAG MCP server that enables natural language queries over text and visual content (PDFs, images, etc.) with verifiable citations, easily run via npx with a Calypso API key.

An MCP server that serves documentation and enables AI-powered search, Q\&A, and document analysis for developer tools and guides.