Lahari Chowtoori
Open Source TPM, AI/ML
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Lahari is an Open Source TPM for AI/ML at AWS, working at the intersection of open source and AI. She drives initiatives bringing tools like Jupyter AI and Strands Agents to global developer communities, and tracks the open source AI ecosystem including MCP, LangChain, and agent frameworks to quantify protocol adoption trends. She's spoken at OSS Summit EU, PyTorch Conference, JupyterCon, OSS NA, and MCP Dev Summit.
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Your MCP Server Will Probably Be Abandoned. Or Not.
Here's what's going to happen: MCP takes off. Hundreds of MCP servers get built. Most of them end up unmaintained within two years and then issues pile up, PRs go stale, the original author moves on.
I have spent time digging through MCPZoo, a dataset of 56,000+ MCP servers, and the warning signs are already there. Repos with READMEs that just say "install and run." Projects with one contributor and no activity in months. Issues sitting unanswered. The ecosystem is growing fast, but a lot of what's being built has "abandoned in 6 months" written all over it.
I'm sure some of you have tried contributing to these projects. Couldn't run the tests. Couldn't understand the structure. Couldn't tell if anyone was still around. That friction isn't just annoying, it's why maintainers burn out and contributors disappear.
In this talk, I'll break down what makes an MCP server thrive or die. Projects die when newcomers can't onboard, can't run tests, can't understand the structure. The ones that survive do specific things: working CI from day one, a README that gets someone running in under 5 minutes, clear contributor guidelines. I'll show you how to set up your own projects to last.
AI Can Contribute. It Can't Lead.
AI is doing real work in open source. Answering questions, reviewing PRs, writing patches. Some communities ban it, others label it. Most will accept it because policing AI is exhausting and the tooling is useful.
Here's what bothers me. Everyone argues about allowing AI contributions. Nobody talks about what we lose when humans stop doing the work. AI can write code. But it can't show up to community calls for two years. It can't help someone push their first PR. It can't convince a burned-out maintainer to stay. Leadership isn't a pull request. It's a relationship.
We have a leadership problem. Projects lose maintainers faster than they grow new ones. AI makes it worse by paving over entry-level work that used to get people involved.
The policy landscape is messy. Apache requires disclosure. OpenTelemetry treats AI as a tool. Linux Kernel won't accept patches without a human behind them. These policies reveal how communities define contribution, accountability, and belonging.
My argument is simple. Stop fighting AI. Start investing in what it can't do. Mentoring. Building trust. Growing leaders. That's what's at risk.
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