Discover ordinary-claude-skills, a local-first collection of 600+ prompt packages that specialize Claude AI with domain skills, integrated via MCP filesystem for lazy loading.
This Python MCP server wraps Meta’s Facebook Ads API into 20+ tools, letting AI agents query ad data conversationally. Setup is simple with a single server.py and token auth.
Blueprint MCP is a Python MCP server that generates system diagrams from codebases asynchronously using Google’s Nano Banana Pro model, integrated with Arcade MCP and Cursor IDE.
Alpaca MCP Server v2 rewrites the official MCP server using FastMCP and OpenAPI tools, exposing Alpaca’s Trading API via MCP for AI clients with env-var config and toolset filtering.
Apify MCP Server exposes 8,000+ web automation tools as MCP tools to AI agents, featuring agentic payments allowing autonomous crypto payments for tool execution. Supports HTTPS and local modes.
LobeHub offers a TypeScript-based AI agent platform with a unique MCP plugin system for integrating 10,000+ skills and collaborative multi-agent workflows. Explore its architecture and developer experience.
awesome-mcp-servers is a curated list of Model Context Protocol (MCP) servers enabling AI models to interact securely with resources. This article explores its architecture, strengths, and how to navigate it.
The WordPress MCP Adapter converts WordPress’s Abilities API into the Model Context Protocol, enabling AI agents to interact with WordPress seamlessly through standardized tools and prompts.
Google Gemini CLI is a TypeScript-based terminal AI agent offering direct Gemini model access, extensibility via MCP, and advanced features like Google Search grounding. Here’s how it works and who should use it.
Langflow offers a Python-based visual platform to build and deploy AI agents and workflows with multi-agent orchestration, vector DB support, and enterprise features.
TrendRadar is a self-hosted AI-driven tool for multi-platform trend monitoring, using MCP architecture for advanced language analysis and smart push notifications across popular messaging platforms.
Context7 tackles LLM hallucinations by injecting up-to-date, version-specific library docs directly into AI coding agents’ context via CLI or MCP server integration.
Awesome LLM Apps offers 100+ runnable AI agent and RAG templates for quick LLM app development. It supports multiple providers and advanced multi-agent patterns with minimal setup.
