"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.

Enables authenticated, explicit-text message exchange between independent clients through a durable queue with idempotent sends, replay-safe inbox reads, bounded conversations, pause/reset controls, and client-driven polling.

Enables AI clients to read and search macOS Messages history through a read-only MCP interface.

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.

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.

Call OpenAI Codex from Claude Code for independent second opinions, structured code review, and delegated coding tasks through a FastMCP plugin that drives the codex CLI safely.

Enables AI agents and MCP clients to drive real Chrome, Edge, Brave, and Firefox browsers through native automation protocols. It exposes tools for navigation, page snapshots, form filling, clicks, screenshots, console/network inspection, and tab management.

MCP server that turns raw in-app screenshots into beautiful, store-ready marketing images for the iOS App Store and Google Play.

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.

MCP server for looking up apps, reviews, ratings, charts, in-app purchases, privacy details, and version history on Apple's App Store. It requires no API key.

Enables MCP clients to open websites, capture screenshots at multiple breakpoints, and run automated design audits for issues like overflow, small tap targets, low contrast, missing alt text, tiny text, and clipped content.

An MCP relay that adds a use_jev tool to every connected server, letting the Jev model autonomously select and execute tool calls while the calling model supplies any required text values. It enables agents to delegate multi-step tool use across all configured MCP servers through a single unified interface.

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 AI agents to manage Google Play releases, store listings, testers, reviews, and app bundles through the official Google Play Developer API.

Enables AI agents to manage App Store Connect releases, metadata, TestFlight, screenshots, and customer reviews through Apple's official API.

Enables AI agents to debug and repair historical Solaris/SPARC systems by providing an out-of-band control plane with guest DTrace, QEMU monitor access, SPARC-aware GDB, host eBPF/perf tracing, and an immutable evidence ledger for cross-layer hypothesis testing.

MCP server providing durable Substrate organizational memory tools, including search, read, query, ingest, remember, and sync. It integrates with Codex to automatically capture completed turns and session boundaries for persistent memory.

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 Code to control Firefox through tools for tabs, navigation, clicks, typing, scrolling, screenshots, page reading, forms, JavaScript, and console/network logs.

MCP server for managing and controlling multiple isolated Chrome/Edge browser instances, exposing tools for navigation, screenshots, clicking, form filling, and JavaScript execution to AI clients.

Enables Claude and other MCP clients to query live online-store product, order, sales, stock, and customer data in plain English, with secure read-only defaults, masked customer information, capped results, and audit logging.

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 agents to browse a yoga apparel catalog and complete purchases through authenticated JSON/MCP checkout, with identity, mandate, budget, and payment gates.

Enables LLM applications and agents to persist and recall scoped memories in a local SQLite store, with semantic/hybrid/metadata search, review-first corrections and summaries, and controlled export, backup, and purge operations over stdio.

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.