"An in-memory data store for caching and message brokering" matching MCP servers:

Enables AI tools like GitHub Copilot to manage and persist context using a local JSON-based memory store. Provides CLI, MCP server, and VS Code integration for storing, retrieving, and managing context entries.

Enables storing, searching, and compressing contextual memories for LLM interactions, with tools for memory management and context injection.

Real-time push notifications and alert sounds free you from staring at the screen. While the AI works, you can comfortably enjoy a cup of coffee.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

Provides AI coding assistants with persistent memory, AST-based project indexing, and tools for live context management and hallucination detection. It enables saving lessons to local files, trimming conversation history, and verifying code symbols to prevent errors.

Commit Message AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

A Windows-optimized server providing universal data analytics for JSON and CSV files through over 32 tools including schema discovery and interactive visualizations. It is specifically designed for seamless integration with Claude Desktop on Windows.

A Rust MCP stdio server for durable project-local AI notes, enabling agents to store, search, and manage verified facts, decisions, and conventions.

Free App Store competitive intelligence for Claude — rival downloads, revenue, and ASO keywords. MCP server, no subscription.

An MCP server that scans code repositories for app store rejection risks by mapping API usage to required declarations and policy deadlines, enabling agents to catch issues before submission.

An MCP server that connects to the Google Play Developer API to deploy apps, manage releases, respond to reviews, and monitor app health through an AI assistant.

Generates beautiful App Store and Play Store screenshots by inserting app images into iPhone/iPad mockup frames with customizable text overlays and gradient backgrounds. Supports multiple device types and batch generation with both free and pro subscription tiers.

Manage multiple Shopify stores through 55 tools with explicit store selection and separate credentials. Includes products, collections, inventory, discounts, images, reports, interactive results, and temporary storefronts with Shopify claim links.

Enables academic research through paper search across multiple databases (IACR, CryptoBib, Crossref, Google Scholar), PDF processing, and GitHub repository browsing. Features modular architecture with FastMCP-based proxy server routing to specialized academic tools.

Enables AI agents to inspect UI screen recordings as token-efficient image sheets with changed regions boxed, single-frame flicker flagged, and speech aligned to frames. Exposes watch_video and zoom_video tools so agents can pull dense keyframes across any time range or one sharp full-resolution frame, all processed locally.

A local-only MCP server that uses SQLite to store, search, and manage a personal library of AI prompts. It enables developers to organize and reuse prompts across multiple AI clients like Claude and Cursor while keeping all data on their local machine.

Enables Claude to read and manage App Store listings, builds, TestFlight testers, localized store texts, screenshots, and customer reviews through Apple's official App Store Connect API, with read-only access by default and explicit approval for each change.

Enables AI assistants to inspect Chrome Web Store status, metrics, ratings, and reviews, and to upload, publish, roll back, or adjust rollout of extension versions, with human confirmation for changes that affect users.

Enables AI coding assistants to scan an iOS, Android, Flutter, React Native or Expo project for App Store and Google Play rejection risks, returning deterministic findings that cite the guideline section, link to the official Apple or Google page and explain how to fix each problem. Nothing leaves the machine and no AI is used in the checks.

Enables any MCP client to drive the user's real Chrome profile through a Chrome extension bridge, with tools for navigation, accessibility snapshots, ref-based interactions, console/network reading, screenshots, tab management, and restricted script evaluation.

A comprehensive MCP server for IT, DBA, and developer tasks, enabling error resolution, task automation, performance monitoring, automated documentation, and configuration management.

MCP server for App Store Connect that enables reading app/version data, analytics reports, sales/finance reports, and safely preparing metadata updates via natural language.

Enables users to describe an LLM fine-tuning job and receive ranked, task-aware GPU recommendations with estimated VRAM/FLOPs, cost, and runtime across more than ten cloud providers.

Enables users to describe an LLM fine-tuning job and receive the cheapest, fastest, or most balanced GPU options across multiple cloud providers by calculating required VRAM and FLOPs.

Enables users to describe an LLM fine-tuning job and receive ranked GPU recommendations across a dozen cloud providers based on estimated VRAM/FLOPs, live pricing, cost, and speed. It returns cheapest, fastest, and balanced hardware options without manual comparison.

Enables users to describe an LLM fine-tuning job once and get ranked GPU hardware recommendations with estimated VRAM/FLOPs, cost, and runtime across a dozen cloud providers.

It enables users to describe an LLM fine-tuning workload once and automatically estimates required VRAM/FLOPs, compares live GPU pricing across cloud providers, and returns ranked cheapest, fastest, or balanced hardware recommendations.

Enables users to describe an LLM fine-tuning workload and receive ranked, task-aware GPU recommendations by estimating required VRAM/FLOPs and comparing live pricing across a dozen cloud providers.

Enables users to describe an LLM fine-tuning job once and receive ranked GPU recommendations across many cloud providers based on estimated VRAM/FLOPs, cost, and runtime.

Enables users to describe a fine-tuning workload and receive ranked GPU cloud recommendations based on required VRAM/FLOPs, cost, and runtime across multiple providers.