How Alpic Is Building Model Context Protocol (MCP) Infrastructure For A New Agentic Internet
When Pierre-Louis Theron describes the opportunity in front of his new company, Alpic, he offers a statement with some lofty aspirations.
Theron believes that Model Context Protocol (MCP), introduced less than a year ago by Anthropic, represents the missing link in AI adoption. Instead of AI models clumsily scraping web pages or fumbling through APIs, MCP allows autonomous AI agents to interact directly with software and services through a structured interface.
“I really see it as like the early days of the internet,” he said. “Almost every single company in the world will build an MCP server. MCP is the way of communicating between these clients facing the user and the back end, the same way HTTP was interfacing with your browser.”
Just as websites became essential in the 1990s, he believes MCP servers will soon be universal. That conviction landed Alpic a $6 million pre-seed round led by Partech, with participation from K5 Global, Irregular Expression, Yellow, Drysdale, Kima Ventures, and Galion.exe, along with prominent founders from companies like Mistral, Datadog, and Dataiku.
Alpic represents a bet on a fundamental shift in how we'll use the internet. Instead of humans clicking through websites, AI agents will directly access services to book flights, update CRM records, or manage expenses on our behalf. MCP is poised to be the operating system for AI agents to make that happen. Alpic wants to deliver the infrastructure that enables companies to leverage MCP.
The stakes are high. If he's right, companies that fail to build these agent interfaces risk being left out of an increasingly AI-mediated internet.
"I believe that in the next 12 months, or the next two years, almost every single company in the world will build an MCP server," Theron said.
From Video Streaming to AI Infrastructure
Alpic's founding team brings extensive infrastructure experience to this ambitious vision. In 2013, Theron co-founded a peer-to-peer video streaming startup called Steamroot. His co-founders included Charles Sonigo and Nikolay Rodionov. They were joined a year later by CMO Erica Beavers.
Lumen Technologies acquired Streamroot, where the team spent years scaling video infrastructure. They eventually left and drifted on to other companies and projects before regrouping to tackle the next major transition: the move toward AI agents. The quartet was joined by fifth co-founder Frédéric Barthelet.
The timing proved fortuitous.
When Anthropic released Model Context Protocol in November 2024, Theron and his team were among the first to recognize its potential. "We were one of the first few people actually looking at it and playing with the technology, and we went into this MCP rabbit hole for the first six months of the year," he said.
The Protocol Wars
MCP represents something of a paradigm shift for AI capabilities. Until now, AI models excelled at generating text but struggled with taking actions in the real world, relying on clunky workarounds like web scraping or navigating human-designed interfaces. MCP offers a structured, secure way for AI agents to connect directly to external services.
The protocol creates two components: MCP servers, which act as agent-facing frontends for applications, and MCP clients, typically integrated into chatbots like ChatGPT, Claude, or Cursor. This architecture could enable a future where, instead of browsing airline websites, users simply tell an AI agent their travel preferences and let it handle the booking process directly.
There have been several competing protocols released, but MCP has emerged as the clear favorite so far.
“The critical thing is to have this layer between your systems and AI,” Theron said. “Today, MCP is the only thing that has any traction. This is the best thing we have today, and it works pretty great.”
Real Infrastructure Challenges
Building MCP servers introduces complex infrastructure challenges that go far beyond simply creating an API.
"Authentication, user experience, payments, and developer workflows look completely different when the user is an AI agent. We're only beginning to understand how much the internet will change," Theron noted. "Alpic's mission is to provide the infrastructure to make those connections seamless."
Alpic's platform addresses three core areas: deployment and hosting, security and authentication, and monitoring and analytics. The security piece proves particularly thorny. How do you manage authentication when an AI agent, rather than a human, is accessing systems on behalf of a user? What permissions should that agent have? How do you monitor and evaluate agent behavior to improve the user experience?
The early market traction suggests real demand for these solutions.
"In terms of our customers, it can be really any business that has a service that is consumed online, that a human can interact with online," Beavers said. The company sees interest from B2C companies like flight booking and restaurant reservation services, as well as B2B SaaS platforms with dashboards users currently access manually.
Developer-focused tools are seeing the earliest adoption, with integrations connecting coding assistants like Cursor to services like GitHub and Linear. But the use cases are expanding rapidly into expense management, CRM systems, and ERPs as companies experiment with agent-accessible interfaces.
Moving at AI Startup Speed
Alpic's timeline reflects the breakneck pace of AI infrastructure development. The company incorporated in July 2025 and launched its public beta platform just last week, alongside announcing the funding round. "We have customers up and running on the platform that's deployed MCP servers," Theron said.
The rapid development cycle means the current platform offers basic functionality, such as one-click deployment, initial analytics showing which tools are being called and which clients are being used, and authentication setup assistance. But the team is already gathering feedback for the next wave of features as sign-ups pour in following the public launch.
Competitive Landscape
Alpic faces competition from multiple directions. Cloud giants like AWS could easily add MCP hosting to their service portfolios, while existing infrastructure players like Vercel and Cloudflare could also explore the space. AI companies themselves represent another potential threat, though Theron sees them more as distribution partners than direct competitors.
The key differentiator for Alpic, Theron argued, lies in developer experience and specialization. Just as Vercel built a successful business on top of AWS by abstracting complexity and providing superior tooling, Alpic aims to make MCP deployment as simple as possible while providing the specialized analytics and security features that agent-focused applications require.
The Long Game
With this pre-seed funding, Alpic plans to focus intensively on reaching product-market fit and building revenue. The company may skip a traditional seed round entirely, jumping directly to a larger Series A as the market develops.
Whether Alpic's vision of an agentic internet materializes remains to be seen. But with major AI labs adopting MCP and early customers already seeing unexpected traffic to their agent interfaces, the infrastructure layer for this new paradigm is already in demand.
"Obviously, we believe that this could be so big that a massive player gonna emerge from this," Theron said. "We're really building a new internet. The traffic is shifting from humans going to websites to AI going to websites and doing things for you. We are in this for the long run."