"A platform for deploying a website online" matching MCP servers:

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

Production-ready MCP server providing RAG, hierarchical memory, and 8+ tools for AI agents via the Model Context Protocol.

Exposes a standardized web search tool via Brave Search for MCP clients like Codex, Claude, and Cursor, returning stable JSON.

A Python-based MCP server that enables document-based question answering by processing PDF, TXT, and Markdown files through OpenAI's API. It provides hallucination-free responses based strictly on document content using semantic search and includes a web interface for management.

Enables document-based question answering using OpenAI's GPT-4 with semantic search and embeddings. Upload PDF, TXT, or Markdown files and get answers strictly based on document content with source attribution and confidence scores.

Enables AI agents to fetch webpages locally, extract main content, and convert it into clean, token-efficient Markdown with preserved links. Supports configurable multi-page crawling, caching, robots.txt compliance, and optional chunking for downstream processing.

Fetches web pages, strips noise, and converts them to clean Markdown with preserved links and optional multi-page crawling, enabling token-efficient web content extraction for AI agents and LLM pipelines.

Enables AI agents and LLM pipelines to fetch and crawl webpages, strip extraneous content, and convert them into clean, link-preserving Markdown for fast, token-efficient scraping.

Fetches webpages—and optionally crawls linked pages up to a configurable depth—then strips noise and converts the content into clean, token-efficient Markdown with links preserved. It caches results, respects robots.txt, and streams content for low memory use, making it suited for feeding AI agents, IDEs, and LLM pipelines readable web content.

Enables AI agents and LLM pipelines to fetch webpages or crawl sites locally and convert the content into clean, token-efficient Markdown with links preserved. Includes caching, robots.txt-aware rate limiting, concurrent depth crawling, and optional chunking for downstream processing.

Enables AI agents to fetch web pages locally, strip noise, and convert content to clean Markdown while preserving links, with caching and optional multi-page crawling for token-efficient scraping.

Enables MCP-based access to Adhoc documentation, providing search, content retrieval, and feedback issue creation with audience gating and leak protection.

Enables support engineers to analyze tickets against a help center with cited retrieval, role-gated and human-confirmed actions, and safety-gated evaluation.

Enables users to ingest PDF/DOCX/TXT/MD documents and ask natural language questions about them, using local embeddings and Groq-powered retrieval-augmented generation.

Enables AI agents to fetch one or many web pages concurrently and receive clean, LLM-ready Markdown with navigation, ads and boilerplate stripped away, plus extracted metadata such as title, description, author, Open Graph tags and canonical URL. It runs locally over stdio with no API key or account, requiring only a single command.

This server enables users to download entire websites and their assets for offline access, supporting configurable depth and concurrency settings.

Enables AI agents to maintain persistent, searchable two-layer memory with 37 tools, hybrid search, knowledge graphs, and enterprise features like authentication and backups.

MCP server for integrating manufacturing systems (MES/ERP/quality/maintenance) with LLM agents, enabling event ingestion, incident triage, approval workflows, and RAG-based knowledge retrieval.

This read-only MCP Server allows you to connect to Exact Online data from Claude Desktop through CData JDBC Drivers. Free (beta) read/write servers available at https://www.cdata.com/solutions/mcp

Enables querying PDF documents using natural language with grounded answers and source citations via a local RAG pipeline.

Enables AI agents to answer Power Platform governance questions — data policies, connectors, environments, Managed Environments, security roles, the CoE Starter Kit and ALM — using hybrid keyword-plus-semantic search over Microsoft's documentation, with a deep link to the exact section behind every answer. It runs locally without API keys, offers read-only search, section-reading and document-listing tools, and connects to Claude, VS Code and Copilot Studio.

MCP server for integrating LightRAG with AI tools. Provides a unified interface for interacting with LightRAG API through the MCP protocol.

Turns any static website into an MCP-searchable knowledge base by deploying a Cloudflare Worker that provides full-text search tools, enabling AI assistants to search and retrieve content from your site.

Enables AI assistants to directly access quant research knowledge, including factor libraries, strategy backtesting, and research reports, through the MCP protocol.

A local-first RAG system that indexes personal documents and enables querying them via an MCP tool, keeping data private with local embeddings.

Enables retrieval-augmented question answering with source-grounded citations, document retrieval, and idempotent ingestion through MCP tools.

Enables MCP hosts like Cursor or Claude to query an enterprise knowledge base via stdio, providing RAG-based answers with cited sources.

提供文档智能问答的MCP服务器，支持查询知识库、获取会话历史和清理会话历史。

Enables governed, read-only SQL analytics, hybrid RAG knowledge search, financial metric calculation, and database schema introspection through MCP, with role-based access control, audit logging, and AI observability.