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

Provides web search and page fetching capabilities using Ollama's API.

Web crawling and RAG implementation that enables AI agents to scrape websites and perform semantic search over the crawled content, storing everything in Supabase for persistent knowledge retrieval.

Enables broad web search for current, time-sensitive information, returning short title, URL, and snippet results rather than full pages. It supports region and result-count parameters through a keyless multi-engine backend.

Enables users to search Reddit by keyword or subreddit, read thread URLs with comments, filter and sort results, and receive flat post and comment rows without needing a Reddit login or API key.

Enables AI agents to search the web with clean page text, crawl websites into Markdown, extract articles and structured data, and monitor Google News and press releases for LLM context and RAG pipelines. It works with MCP clients and uses the user's own Apify API token for pay-per-result data retrieval.

Fetches web content and returns relevant chunks using RAG with semantic chunking, query-based scoring, and LexRank, supporting PDFs and 50+ languages.

A Model Context Protocol server that enables web searching using the Serper API for Google search results, with optional web page content fetching.

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.

Provides multi-provider web search capabilities with fallback chains, semantic reranking, and content extraction for grounded agent retrieval.

Enables AI agents to perform web search, extraction, and research across multiple provider backends with persistent multi-key rotation and auditable routing. Supports MCP, CLI, and Agent Skill entry points.

Enables one-call parallel querying across multiple search engines, aggregating and deduplicating results while automatically falling back to mainland engines when overseas sources are unreachable.

Provides keyless, privacy-focused web search through DuckDuckGo and SearxNG via MCP, with token-efficient tool discovery and caching.

Aggregates security research articles from WeChat, QAX Butian, and Xianzhi community, with optional KimiCode web search. Supports smart deduplication, article fetching, and anti-bot measures.

Provides web crawling and RAG capabilities for AI agents, enabling scraping of websites, storing content in a vector database (Supabase), and performing semantic search over crawled data.

Crawls and indexes documentation websites to Supabase with vector embeddings for RAG, using smart sitemap discovery and Jina AI for fast content extraction with multi-project support.

Crawl any documentation site and return heading-bounded, LLM-ready chunks with source metadata for Pinecone, Chroma, pgvector, LangChain, or LlamaIndex.

A database-agnostic MCP server that integrates web crawling with Retrieval Augmented Generation, supporting multiple AI providers and vector database backends for flexible and intelligent content retrieval.

Enables semantic search and retrieval-augmented generation (RAG) using Qdrant vector database. Supports indexing documents from URLs and local directories, with flexible embedding options using Ollama or OpenAI.

A local MCP server that gives Claude Code web search capabilities using DuckDuckGo, enabling discovery of URLs from natural language queries.

Enables finding information online, reading web pages, finding images, capturing screenshots, and performing multi-source research with per-answer confidence.

Provides an MCP server that enables web search and page extraction across multiple providers with automatic failover and quota rotation, plus a local dashboard for managing keys, engine order, and request history.

A local-first, no-API-key MCP server that enables LLMs to search the web, fetch pages, and read documents using multiple engines and smart fallbacks.

Enables AI agents to perform web search, page fetching, and multi-source research via the official search and fetch API, with deduplication, content limits, caching, and rate limiting.

MCP server for Google Search using a logged-in browser profile, delivering personalized, ad-free results with advanced operators and pagination. It also fetches web pages as markdown through the same browser session.

Job search mechanics for an AI assistant: search Arbeitnow/Adzuna/JSearch, fetch a single job posting, render a CV to PDF, lint it against your own configurable anti-fabrication rules, and log the outcome to your application registry. Never auto-applies.

Enables web searches through DuckDuckGo without an API key and extracts readable main content from web pages.

Enables MCP-compatible agents to perform web searches via the agent-web-search engine, returning ranked results with sources.

Enables LLM clients to run Brave LLM Context web searches and fetch readable markdown extracts from URLs, including specialized site extraction, PDF text, raw mode, and pagination.

Free web search, web-page reading as Markdown, and llms.txt documentation retrieval for MCP clients. Runs locally with Node.js over stdio using @alkasima/alka-search-mcp. Searches DuckDuckGo, Mojeek, and Brave; default providers require no API key. Website and provider availability may vary.

Enables Claude to perform real-time web searches and fetch web page content via MCP, using OpenAI-compatible APIs with optional Tavily or Firecrawl engines.