by metorial · MCP Server · ★ 210
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Metorial Platform The open source integration platform for agentic AI. Connect any AI model to thousands of APIs, data sources, and tools with a single function call. [!TIP] Skip the setup and go hosted: The fasted, simplest and most reliable way to use Metorial is to sign up to our hosted platform. ➡️ Get Started (for free) Introduction The Metorial Platform is an open source integration platform that makes it easy for developers to connect their AI applications to external data sources, APIs, and tools. It's built to scale to tens or hundreds of thousands of concurrent MCP connections, making it ready for enterprise-grade applications. If you're interested in the MCP serves that power Metorial, check out the MCP server catalog. Features ✨ One-liner SDKs: Connect your AI model to any API, data source, or tool with a single function call. 🛠️ Powered by MCP: Metorial is built on the Model Context Protocol, a standard for connecting AI models to external data and tools. 🚀 Get started in minutes: Metorial is designed to be easy to use, with a simple setup process and a unified interface for all your AI integrations. 🕊️ Self-hosting: Metorial's source code is hosted on GitHub and yo
| Stars | 210 |
| Forks | 22 |
| Language | TypeScript |
| Category | MCP Server |
| Quality Score | 39.422/100 |
| Open Issues | 7 |
| Last Updated | 2026-05-21 |
| Created | 2025-05-03 |
| Platforms | mcp, node |
| Est. Tokens | ~7015k |
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metorial-platform is The engine powering hundreds of thousands of MCP connections 🤖 🔥. It is categorized as a MCP Server with 210 GitHub stars.
metorial-platform is primarily written in TypeScript. It covers topics such as agentic-ai, ai, mcp.
You can find installation instructions and usage details in the metorial-platform GitHub repository at github.com/metorial/metorial-platform. The project has 210 stars and 22 forks, indicating an active community.
The top alternatives to metorial-platform on Agent Skills Hub include agentic-radar, mcp-client-for-ollama, wren-engine. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.