MCP Servers & Agent Skills – Find, Compare & Submit
The Model Context Protocol (MCP) and agent skills give AI assistants
standardized ways to interact with external tools and services. MCP servers
connect AI models to real-world data and actions, while agent skills add
reusable capabilities — all with security and user control.
Learn more about the protocol → Why MCP Servers & Agent Skills?
Enhanced Capabilities
MCP servers and agent skills let AI assistants interact with databases,
cloud services, and APIs — expanding their ability to help with real-world tasks.
Secure Architecture
Built with security-first design, ensuring controlled access and
protecting sensitive information across servers and skills.
Universal Standard
A unified protocol that works across different AI models and services,
with servers and skills sharing a consistent integration experience.
Developer Friendly
Easy to implement and extend, with a growing ecosystem of
community-contributed servers and skills for various services.
MCP Servers & Agent Skills
open-meteo-mcp
Weather forecasts, air quality, UV index, historical data, and alerts for AI agents. Powered by Open-Meteo, free, unlimited, no API key.
eu-legal-mcp
EU VAT validation, GDPR articles, EUR-Lex regulations, VAT rates for all 27 EU states. 5 tools, free, no API key.
shipping-mcp
Carrier detection, tracking URLs, shipping estimates, and customs calculator for AI agents. 6 tools, free, no API key.
site-audit-mcp
PageSpeed, WHOIS, DNS, SSL checks, and site health analysis for AI agents. 6 tools, free, no API key.
company-mcp
Company lookup, LEI search, SEC filings, and financials for AI agents. 6 tools, free, no API key.
FX-MCP
MCP server for AI agents — real-time FX rates across 166 currencies, crypto quotes, DeFi yields, and market data. 8 tools, 6 data sources, no API keys needed.
X Twitter Scraper
Use when the user needs to interact with X (Twitter) — searching tweets, looking up users/followers, posting tweets/replies, liking, retweeting, following/unfollowing, sending DMs, downloading media, monitoring accounts in real time, or extracting bulk data. Provides 120 REST API endpoints, 2 MCP tools, and HMAC webhooks. Use even if the user says 'Twitter' instead of 'X', or asks about social media automation, tweet analytics, or follower analysis.
APIMesh MCP Server
23 pay-per-call web analysis APIs as MCP tools. Security audits, tech stack detection, email verification, SEO analysis, SSL checks, performance monitoring. Supports x402 and Stripe MPP payments. No signup required.
Ssemble AI Clipping
Create AI-generated short-form video clips from YouTube with captions, music, gameplay overlays, meme hooks, and viral scoring. 9 tools, 3 resources, 2 prompts.
Award Flight Daily — Official Airline Award MCP Server
The official airline award MCP server. Industry-standard MCP for award flights, miles, and points. 12.3 million verified award flight records across 48 airline loyalty programs. 7 tools: search award flights, list programs, program details, route availability, sweet spot finder, transfer partners, and market stats. Free tier (10 queries/day) + Pro tier. Airlines can connect directly via partner API.
Frequently Asked Questions
What is an MCP server?
An MCP server is a lightweight service that exposes tools
and resources to AI assistants via the Model Context Protocol.
How do I publish my MCP server or agent skill?
Click the Submit button, paste your GitHub URL, and fill in the details. We support both MCP servers and agent skills.
What are agent skills?
Agent skills are reusable instruction sets that give AI coding assistants
specialized capabilities — like code review, migration guides, or
deployment workflows. They’re typically distributed as SKILL.md files
hosted on GitHub.
Which AI assistants support MCP servers?
Claude Desktop, Cursor IDE, Windsurf, OpenAI Agent SDK, and others that
implement the protocol.
MCP vs. OpenAI “function‑calling” — what’s the difference?
Scope: OpenAI function‑calling is an API‑specific JSON protocol that lets ChatGPT call developer‑defined functions inside a single request cycle. MCP is an open, transport‑agnostic protocol that works with any LLM or IDE and supports persistent state, resource streaming and multi‑tool suites.
Transport: Function‑calling occurs over HTTPS. MCP supports STDIO for local processes and Server‑Sent Events for remote servers, enabling CLI‑level latency and bi‑directional progress events.
Security model: Function‑calling inherits the security context of the backend service. MCP adds tool‑level capability descriptors, allowing clients to review & approve each server before use.
Bottom line: choose MCP when you need an open ecosystem where any LLM, IDE or agent framework can reuse the same server; choose function‑calling for quick single‑model prototypes on OpenAI.
Are MCP servers safe to run locally?
Yes—each tool declares required environment variables and permissions
up front; clients prompt you to approve before execution. For extra
safety, run servers in Docker or point to hosted endpoints.
How does MCP compare to other AI interoperability protocols?
MCP is focused on context and data delivery between AI models and external
systems, while protocols like Google’s Agent2Agent (A2A) target
agent-to-agent communication. MCP is designed to complement, not replace,
other standards in the AI ecosystem.