Metorial
Vercel for MCP
TL;DR
Metorial gets AI agents into production in hours, not weeks. 600+ MCP servers, ready to deploy in just three clicks.
We're the only serverless MCP platform that can handle hibernation with sub-second cold starts as well as OAuth, enterprise-grade security, and per-user isolation.
Starred by more than 3000 GitHub devs. Used by engineers at FAANG, the Big 4, and American Express. Currently piloting with leading startups and Fortune 500s.
The Problem
The AI space is evolving rapidly; companies can’t afford to wast time building integrations. MCP has become the standard for connecting LLMs to external tools, but deploying MCP in production is painful. Running MCP servers yourself means managing Docker configs, handling OAuth flows, and debugging without observability. Writing serious integrations manually wastes weeks in digging through API documentation. Developers want to ship agents now, not build infrastructure for months.
Our Solution
Deploy any of our 600+ MCP servers in just three clicks -- we even handle OAuth. Our SDKs let you connect your agents to the hosted MCP servers in a single function call. Our serverless runtime solves scaling and security issues for multi-tenant deployments by providing sub-second cold starts with per-user isolation.
Building a complex agent with Metorial looks as simple as this:
Demo
Our Story
When MCP was released, we quickly understood its value in offering a natural language interface for LLMs to execute external tools autonomously. But when we tried to take MCP beyond client-side apps like Cursor, setting up the infra for security, scaling, and per-user isolation turned out to be a massive time sink. That’s when it clicked: developers like us need a turn-key solution to plug integrations into their agents. So we pivoted from hacking infra together to building Metorial.
The Ask
Building AI agents or using MCP?
Try metorial.com. We can help you integrate Metorial and add any MCP servers you need.
Book a call: cal.com/karim-rahme/launch-yc
Email us: founders@metorial.com
How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?)
Tobias and Wen have been friends for over 10 years. They met in a top technical high school in Austria where they worked on many projects together. Later, they co-lead the technical development at Valicit, a ticketing startup based in Abu Dhabi.
What's the history of your company from getting started until the present day? What were the big inflection points?
When MCP was released, we quickly understood its value in offering a natural language interface for LLMs to execute external tools autonomously.
But when we tried to take MCP beyond client-side apps like Cursor, setting up the infra for security and scaling turned out to be a massive time sink.
Thatʼs when it clicked: developers like us need a turn-key solution to plug MCP into their agents.
So we pivoted from hacking infra together to building Metorial: the Vercel for MCP.
What is the core problem you are solving? Why is this a big problem? What made you decide to work on it?
Integrations transform LLMs from simple chatbots into agents that can perform real tasks.
Recently, MCP has become the standard for connecting AI agents to external tools.
MCP works great locally, but production deployments are painful.
Running MCP servers in production means managing Docker configs, handling OAuth flows, and debugging issues without proper observability.
Developers want to ship agents now, not build infrastructure for months.
