A package that logs a funny story about MCP servers.
MCP Store Gateway — Syncs your installed MCPs from mcpclaudecode.com into Claude Code
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In-memory entitlement store for Stipend — for tests, local dev, and the `stipend dev` CLI.
ZKshare stdio MCP: store/prove/share, semantic search, sandbox proxy to HTTPS /api/v1/context.
Firestore-backed EntitlementStore and DeliveryStore for Stipend (v1.0 default).
Apify MCP Server
Backwards compatible shim for React's useSyncExternalStore. Works with any React that supports hooks.
MCP server for Google Play and App Store scraping
Playwright Tools for MCP
Lightweight core CLI surface for Claude Flow — memory + hooks commands only. Designed to load fast on cold npx cache (<5s) so plugin skills don't race the 30s MCP-startup timeout. The full @claude-flow/cli metapackage lazy-loads everything else on top of
Model Context Protocol implementation for TypeScript
CLI to install MCPs from MCP Store into Claude Code
Invoke scoped data storage for AWS Lambda Node.js Runtime Environment
Help agents automatically write and test stories for your UI components
The official TypeScript library for the Cloudflare API
A TypeScript SSE proxy for MCP servers that use stdio transport.
Anthropic Sandbox Runtime (ASRT) - A general-purpose tool for wrapping security boundaries around arbitrary processes
A high-level API to control headless Chrome over the DevTools Protocol
MCP server for Chrome DevTools
MCP server for Context7
Easily spin up Model Context Protocol (MCP) servers using Fastify
TypeScript definitions for use-sync-external-store
MCP server for interacting with Cloudflare API
Rails Engine that captures exceptions, stores them in your database with rich context, and exposes error data via a bundled MCP server so AI agents can triage, resolve, and fix errors autonomously.
llm.rb is Ruby's most capable AI runtime. It runs on Ruby's standard library by default. loads optional pieces only when needed, and offers a single runtime for providers, agents, tools, skills, MCP, A2A (Agent2Agent), RAG (vector stores & embeddings), streaming, files, and persisted state. As a bonus, llm.rb is also available for mruby. It supports OpenAI, OpenAI-compatible endpoints, Anthropic, Google Gemini, DeepSeek, xAI, Z.ai, AWS Bedrock, Ollama, and llama.cpp. It also includes built-in ActiveRecord and Sequel support, plus concurrent tool execution through threads, tasks (via async gem), fibers, ractors, and fork (via xchan.rb gem).
RailsLLM integrates the llm.rb runtime and its features into Rails. RailsLLM extends the builtin ActiveRecord support available to the llm.rb runtime with a Rails integration that includes generators for getting set up quickly, and an engine for a stream-capable chat interface that can be extended with your own tools. The llm.rb runtime runs on Ruby's standard library by default. loads optional pieces only when needed, and offers a single runtime for providers, agents, tools, skills, MCP, A2A (Agent2Agent), RAG (vector stores & embeddings), streaming, files, and persisted state.
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