A TypeScript boilerplate for building a remote Cloudflare MCP server with user authentication and Stripe integration for paid tools.↗

A TypeScript project intended to bridge MCP (Model Context Protocol) with a UI layer, enabling integration between MCP services and user interfaces.↗

twitter-mcp is a TypeScript-based MCP integration for accessing Twitter functionality via the MCP protocol.↗

Universal Memory MCP that exposes Supermemory to any LLM via the MCP protocol, enabling access to your memories without logins or paywalls. Includes a one-command setup and is built with TypeScript.↗

A Python MCP server that unifies Claude Code, GeminiCLI, and CodexCLI-style workflows with multiple model providers (e.g., Gemini, OpenAI, OpenRouter, Azure, Grok, Ollama, and custom models).↗

love seeing executor & the execution layer post in this video! i'll have a lot more to share on executor this week, it's a bash replacement for your agents and feels like the future of how we give our agents access to tools - try it out! executor.sh↗

The next version of OpenClaw is also an MCP, you can use it instead of Anthropic's message channel MCP to connect to a much wider range of message providers. (I know, this is awkward)↗

Introducing MCP for arXiv Let your research agents stand on the shoulders of giants Fast multi-turn retrieval, keyword search, and embedding search tools across millions of arXiv papers 🚀↗

WebMCP provides a Web-based implementation of MCP (Model Context Protocol), enabling MCP-style integrations in the browser.↗

Provides an agent harness performance optimization system for Claude Code and related coding agents, focusing on skills, instincts, memory, security, and research-first development.↗

*gets up on soap box* With the announcement of this new "code mode" from Anthropic and Cloudflare, I've gotta rant about LLMs, MCP, and tool-calling for a second Let's all remember where this started LLMs were bad at writing JSON So OpenAI asked us to write good JSON schemas…↗

Turn design into code with Claude Code + @figma. Through MCP, Claude sees your mockup at the data level—component hierarchies, design tokens, auto-layout rules—and translates it into production-ready code.↗

Who uses MCP in agents that are not coding agents? And for what?↗

AI Nerds: What’s your coolest MCP workflow?↗

If you’re new to Cursor, this will help you get started right. Here are a few lessons I wish I knew earlier while building MVPs with Cursor, Bolt, and MCP. Not everything I know, but enough to save you weeks of trial and error ↓↗

[New MCP server release] The MCP blogpost is fun to write -- what's more fun to write is an OSS MCP server that gives @cursor_ai agent the ability to send Morse code thru my lamp at home Ask @cursor_ai to communicate using morse code when it's done coding 💡👇 (link below)↗

[New post] 🔥A Deep Dive Into MCP and the Future of AI Tooling APIs were the internet’s first great unifier but AI models lack an equivalent. What are the use cases of MCPs today? Where are the challenges? Here's a technical deep dive & map of the current ecosystem 👇↗

model context protocol (aka MCP) explained simply↗

Cursor + MCP make debugging 10x faster Here’s how I use them to capture errors instantly, fix bugs quicker, and streamline my workflow. Full breakdown:↗

Developers: MCP is about to become extremely relevant as AI needs to connect with real-world data. The problem? Most don't know how to build MCP plugins yet. Here's how to build them with Cline in 3 simple steps using our .clinerules protocol. Thread 🧵↗

Token-efficient MCP adapter for the Pi coding agent, enabling integration with Model Context Protocol (MCP) workflows. Built in TypeScript to support LLM-based coding agents.↗

pi-cursor-sdk lets you run Cursor models inside the pi coding agent using local Cursor SDK agents. It supports native model selection, thinking controls, fast/plan modes, image input, and MCP-bridged pi tools.↗

A local Codex MCP server that scans repositories and generates tldraw product workflow diagrams using TypeScript.↗

Peekaboo is a macOS Swift CLI (with an optional MCP server) that lets AI agents capture screenshots of apps or the entire system, with optional visual question answering via local or remote AI models.↗