"Self-hosted MCP server on Proxmox LXC container accessible remotely from AI clients" matching MCP servers:

Enables interaction with self-hosted LLM models via Ollama and Supabase database operations. Supports text generation, SQL queries, and data storage/retrieval through natural language commands.

Enables read-only searching and retrieval of the official Proxmox VE administration guide via MCP tools and resources, returning cited fragments with source URLs and freshness metadata.

A comprehensive Model Context Protocol (MCP) server implementing the latest MCP specification with tools, resources, prompts, and enhanced sampling capabilities that features HackerNews and GitHub API integrations for AI-powered analysis.

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Reckon Accounts Hosted (beta): https://www.cdata.com/download/download.aspx?sku=KHZK-V&type=beta

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

MCP server that provides secure access to a serverless Markdown wiki on AWS, enabling AI assistants to read, search, and edit pages with space-level permission checks and Bedrock-powered semantic search.

MCP server that enables AI-powered content generation in multiple formats using Google Gemini and Tavily real-time research, accessible via MCP-compatible clients.

Spring AI Playground is a self-hosted web UI platform for building low-code tools and dynamically exposing them via built-in MCP server for AI agents.

Provides a read-only interface to audit and continue coding agent sessions by extracting plans, intents, and edit authorship from history across multiple agents (Claude, Codex, OpenCode, Antigravity, Pi) via MCP, CLI, and Python SDK.

Interact with WebScraping.AI API for web data extraction and scraping

Ingests pdf and epub documents for LLM-retrieval (RAG)

A read-only MCP server that provides document awareness for agents by parsing local files into structured profiles, blocks, chunks, and search results, enabling agents to understand and cite document content without dealing with raw file formats.

Enables AI assistants to intelligently select and switch between different AI models (OpenAI, Anthropic, etc.) within the same conversation based on task requirements. Provides a unified interface for accessing multiple AI providers through a single MCP tool.

Enables natural-language Q&A over multi-source documents (PDF/Markdown/web) with a self-reflective retrieval-augmented agent that cites sources, retries on poor retrieval or grounding, and supports multi-turn memory.

An MCP server with RAG capabilities that provides AI clients secure access to local notes, documents, web pages, and task management tools for developer operational tasks. Features file operations, web scraping with content cleaning, and personal knowledge corpus search functionality.

A simple AI development tool that helps users interact with AI through natural language commands, offering 29 tools across thinking, memory, browser, code quality, planning, and time management capabilities.

Enables XTend developers and agents to search and retrieve canonical XTend documentation, recipes, and kit resources through read-only MCP tools, resources, and prompts served over stateless HTTP.

Enables autonomous agents to securely access and manage virtual file systems, records, schemas, SQL and Mongo queries, and RAG search through scoped MCP tools, while supporting binary transfers via presigned S3 recipes.

Open-source AI memory layer for LLM agents. Importance scoring, temporal decay, hierarchical memory (facts, summaries, themes), YMYL prioritization, and active retrieval with contradiction detection. Supports OpenAI, Anthropic, Ollama. Local-first with SQLite + FAISS.

Enables AI coding agents to persist and retrieve project knowledge using three MCP tools with local vector and full-text search.

Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.

Persistent memory for any AI assistant. Zero token cost until recall. Stores memories in local SQLite, ranks by 6-factor scoring, returns results 79% smaller than JSON. Works with Claude, ChatGPT, Grok, Cursor, Windsurf, and any MCP client.

Generates a complete suite of AI readiness files (llms.txt, ai.txt, schema, RAG indexes) for any website to optimize representation in ChatGPT, Claude, Gemini, and Perplexity.

Exposes Together AI's inference endpoints (chat, image generation, vision, embeddings) as tools callable from MCP clients like Claude Desktop and Cursor.

MCP server for semantic research: search arXiv, fetch papers, and answer questions grounded in the actual paper text via RAG tools, resources, and prompts.

Enables local AI inference for Claude and Cursor through 22 APIs, including summarization, translation, review, classification, RAG, and more, with all data processed on-device.

Enables a unified AI assistant that combines document retrieval (RAG), database queries via MCP tools, and web search, allowing users to ask complex questions and receive answers from multiple enterprise sources.

Enables searching, indexing, and recovering past AI chat sessions and agent actions from local AI coding tools, with optional vector database semantic search and direct filesystem access.

Gives Claude Code and other MCP clients cited answers from a local, code-aware hybrid index of a repository's documentation and source, returning path:line sections linked to the code symbols they name. It also stores session handoff notes and doc/code conflict decisions in a git-backed memory, all running offline with no API calls or data leaving the machine.

Enables browser-based AI services to connect through remote MCP for internal document search, email checking and replies, timecard, sales/project, schedule/task, and operations tasks. It supports multiple AI clients via compatible remote MCP endpoints.