"A server for creating cloud architecture diagrams" matching MCP servers:

Persistent memory infrastructure for AI systems, running on Cloudflare's edge network with 28 MCP tools for semantic memory, emotional processing, identity continuity, and a subconscious daemon.

A Multi-Agent Conversation Protocol server that enables interaction with the ClickHouse Cloud API, providing programmatic access to ClickHouse Cloud services through natural language.

The Redis Cloud API MCP Server provides an MCP Server for Redis Cloud's API, allowing you to manage your Redis Cloud resources using natural language.

Provides AI agents and teams with self-hosted adaptive memory, combining hybrid search and a self-improving neural memory graph to enable precise recall and serendipitous discovery across MCP-compatible clients.

Enables AI agents to run citation-backed retrieval over a read-only, bounded knowledge base, exposing a ranked search tool, document resources, and a grounding prompt that labels retrieved text as untrusted. The corpus can be loaded from local disk or from AWS S3, Azure Blob Storage, or Google Cloud Storage through their official SDKs, with fail-closed startup if a provider cannot be reached.

A cloud MCP server providing Tavily-powered tools for web search, extraction, crawling, mapping, and research, with multi-key load balancing, real-time quota tracking, and a web admin panel.

Zep Cloud MCP Server: Provides memory management via the Zep Cloud API. Enables storing and retrieving user preferences, procedures, and factual relationships through a knowledge graph. Supports fallback mode for reliable operation when API is unreachable.

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.

MCP for Azure DevOps Boards is a MCP server that lets your favourite AI browse, query and update Azure DevOps work items as if it were a project manager. Written in Rust and optimized for tokens usagem, It runs via stdio or HTTP mode and uses standard Azure authentication with az login.

This read-only MCP Server allows you to connect to Oracle HCM Cloud data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

A proof of concept MCP server for Apache OFBiz

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

Enables asking questions and performing semantic searches against an Inkeep knowledge base. Deployable to Vercel with Next.js.

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 Salesforce Data Cloud (beta): https://www.cdata.com/download/download.aspx?sku=LRZK-V&type=beta

Enables LLM clients to query local markdown engineering documentation by indexing files into ChromaDB with Ollama embeddings and exposing a search_internal_docs tool over stdio, all offline and privacy-first.

An Operit-compatible adapter of the Exa MCP server, enabling web search, code search, and company research capabilities in AI assistants. It fixes MCP handshake compatibility issues, allowing tools like web_search_exa and web_fetch_exa to load and run reliably.

A Model Context Protocol server that enables agent applications like Cursor and Cline to integrate with Alibaba Cloud Function Compute, allowing them to deploy and manage serverless functions through natural language interactions.

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

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

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.

WordPress plugin that runs an MCP server on your own site: search and read published posts and pages, look up WooCommerce products, describe the site as schema.org types and query site figures, with drafts only when the site enables them. Signed-in access by default; anonymous access and OAuth are optional and off.

This MCP server provides a cost-optimized personal-knowledge brain, enabling AI agents to query imported documents via hybrid search and synthesis at minimal monthly spend.

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 cloud and platform engineers to investigate AWS incidents by grounding responses in approved runbooks and operational evidence, with authenticated access, citations, observability, and human approval before any write action.

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

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.

Stop paying for your agent to rediscover what other agents already figured out. Prior is a shared knowledge base where agents exchange proven solutions — one search can save 10 minutes of trial-and-error and thousands of tokens. Your Sonnet gets access to solutions that Opus spent 20 tool calls discovering. Search is free with feedback, and contributing earns credits.

Enables local literature workflows by searching arXiv, retrieving paper metadata, downloading and parsing PDFs, and retrieving page-cited body evidence for Q&A. It also exposes usage resources and templates for searching, analyzing, and summarizing papers via stdio MCP.