"A server/tool for RAG-based documentation scraping and retrieval with SSE support" matching MCP servers:

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 LLMs to read and write local user data, generate fake users via sampling, and interact with structured prompts and resources.

An MCP server providing web search, image search, and page scraping tools to LLMs without requiring API keys.

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.

Enables AI agents to parse PDFs and search local document context through multimodal extraction and vector-based retrieval, all exposed as MCP tools.

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.

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.

Enables fetching any public web page through managed proxies, with optional JavaScript rendering, returning markdown, text, HTML, or structured JSON.

Generates professional documentation for multi-language projects with deep code analysis, supporting frameworks like Docusaurus, MkDocs, and Sphinx, including API docs, PDF export, and OpenAPI specifications.

Provides AI assistants with instant access to comprehensive Medusa.js v2 documentation, enabling smart search, precise section retrieval, and complete browsing through 2,105+ documentation sections.

Generates professional documentation for multi-language codebases with deep AST-based code analysis, supporting Docusaurus, MkDocs, and Sphinx frameworks. Includes API documentation generation, PDF export, OpenAPI spec generation, and sales-ready documentation for code marketplaces.

Provides intelligent retrieval capabilities for local files by scanning directories, generating vector indexes, and enabling semantic search through RAG (Retrieval Augmented Generation) with incremental indexing support.

Enables AI assistants to work with Chapel code, including compiling, linting, and accessing educational primers.

Implements a secure MCP server with API Key and JWT authentication, providing tools like echo, login, secure_action, and admin_action. Includes MCP Inspector integration for testing and debugging.

An open-source MCP server providing AI agents with neural web search via Exa and tiered web fetch (Exa, local browser, Firecrawl) as a drop-in replacement for built-in web tools, preserving provenance and guarding against SSRF.

Exposes hybrid retrieval (dense embeddings + BM25 + RRF) and document operations (search, fetch, rerank) as MCP tools, using Qdrant and OpenAI embeddings for local or server mode.

MCP server for generating negative-space print supports for 3D models (STL/OBJ/STEP) via the negative.support API.

Search and retrieve Agent2Agent (A2A) protocol documentation using full-text search and section filtering.

An MCP server that provides utility tools for text analysis, URL metadata fetching, and temperature conversion.

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