"Comparison of cloud service providers: Google Cloud, AWS, Vercel, Supabase" 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.

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.

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.

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.

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

Provides MCP tools to search, retrieve, and answer questions from the public Open Finance Brasil Confluence documentation using BM25-based local indexing.

MCP server for Supabase instances running on Aliyun RDS, enabling AI assistants to interact with your Supabase instance hosted on Aliyun cloud infrastructure.

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/).

Enables AI-powered search and querying of the Vercel AI SDK documentation using natural language questions, with tools for direct similarity search and agent-based answers.

Enables Cursor and Windsurf to safely interact with Supabase databases by providing tools for database management, SQL query execution, and Supabase Management API access with built-in safety controls.

Enables secure interaction with Supabase databases via the PostgREST API, supporting full CRUD operations and stored procedure calls. It utilizes the Dedalus MCP framework to provide encrypted credential handling and just-in-time token exchange.

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 minimal interaction with Supabase databases through 4 essential tools for data querying, mutations, file storage, and user authentication. Designed for 70% less context usage than standard implementations with auto-truncated results and simplified parameters.

Enables real-time communication between applications and AI models using the Model Context Protocol, supporting features like custom tools and multiple transport options for Next.js applications.

Self-hosted service providing unified memory search and write operations across file-based memory, vector embeddings, and the Graphiti temporal knowledge graph, accessible via HTTP API or MCP stdio transport.

Provides search and retrieval over a local database of Pathfinder 2e rules. Enables Claude Code to answer rules questions with cited, accurate answers from fetched entries.

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.

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 production-minded RAG service for MCP that answers questions over your documents with hybrid retrieval, PII redaction, and source citations, packaged for Docker/Kubernetes.

Provides self-hosted, versioned project memory with full-text and vector search, enabling search, retrieval, upsertion, and history management of project entries via MCP tools.

Enables semantic search over local knowledge bases like Obsidian notes, SQLite, and plaintext files, exposing results to Claude via MCP server.

Enables MCP-compatible reasoning agents to perform read-only discovery, retrieval, and exact search across Google Drive, Docs, Sheets, and Slides through a stateless Cloud Run service.

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.

Shrimp Task Manager is a task tool built for AI Agents, emphasizing chain-of-thought, reflection, and style consistency. It converts natural language into structured dev tasks with dependency tracking and iterative refinement, enabling agent-like developer behavior in reasoning AI systems.

An MCP server that enables users to retrieve information from AWS Knowledge Bases using RAG (Retrieval-Augmented Generation) via Bedrock Agent Runtime.

Provides semantic memory and persistent storage for Claude, leveraging ChromaDB and sentence transformers for enhanced search and retrieval capabilities.

An MCP server that uses Groq's API to expose raw chain-of-thought tokens from Qwen's qwq model, enabling LLMs to think step-by-step before responding.