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

Enables retrieval and cleaning of official documentation content for popular AI/Python libraries (uv, langchain, openai, llama-index) through web scraping and LLM-powered content extraction. Uses Serper API for search and Groq API to clean HTML into readable text with source attribution.

Enables retrieval-augmented generation by embedding queries with a chosen provider (e.g., OpenAI) and searching supported vector stores (Pinecone, pgvector) to return relevant content.

Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.

The MCP server provides tools for entity extraction, query refinement, and relevance checking to enhance RAG applications by integrating with OpenAI and Gemini.

An MCP server that retrieves and cleans official documentation for popular AI/Python libraries via web search and LLM processing, exposing a get_docs tool.

MCP server that provides OpenRouter model pricing data, enabling price lookups, trending/cheapest lists, and model searches without an API key.

AI-powered VMware storage management for vSphere. Manage datastores, iSCSI targets, and vSAN via natural language with 11 MCP tools.

An MCP proxy that embeds tool definitions and returns only the top-k semantically relevant tools per query, reducing context usage and routing calls to upstream MCP servers.

Integrates the LINE Messaging API with AI agents via the Model Context Protocol, supporting both stdio and SSE transport protocols. It allows agents to send messages, manage rich menus, and retrieve user profile information for LINE Official Accounts.

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

A Model Context Protocol server that exposes multiple AI tools over SSE transport with JWT-based secure authentication, allowing for dynamic tool registration and session management.

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

MCP server for end-to-end encrypted secret storage and retrieval, enabling LLM agents to fetch secrets by name via one-time URLs while keeping plaintext out of model context and logs.

Enables real-time communication between client and server using Server-Sent Events (SSE) for the Model Context Protocol, specifically built for the Bun JavaScript runtime.

A lightweight MCP data broker that stores large binary payloads under a UUID, enabling MCP clients and agents to exchange massive results without flooding the LLM context window.

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

Enables full-text search and paginated retrieval of indexed documentation (PDFs, Markdown, text) through MCP tools, with filtering by category and file.

A tool discovery MCP server that integrates with Azure DevOps wikis and code-graph-rag to match natural language goals to tools, enabling tool composition and proxy testing.

Enables AI assistants to search and read Azure documentation using full-text search and section filtering, with content retrieval from Microsoft's official Azure docs repository.

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