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Founded by Karim (Wen) Rahme & Tobias Herber
When MCP was released, the team quickly understood its value in offering a natural language interface for LLMs to execute external tools autonomously. But when they 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 them need a turn-key solution to plug integrations into their agents. So they pivoted from hacking infra together to building Metorial.
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.
Deploy any of their 600+ MCP servers in just three clicks -- they even handle OAuth. Metorial's SDKs let you connect your agents to the hosted MCP servers in a single function call. Their 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:
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