At the same time, the protocol's adoption has been 10x faster than Kubernetes, so if you count by this metric, it actually makes sense to donate it now to let others actors in. For instance, without this Google will never fully commit to MCP.
There are lots of small and niche projects under the Linux Foundation. What matters for MCP right now is the vendor neutrality.
Many people only use local MCP resources, which is fine... it provides access to your specific environment.
For me however, it's been great to be able to have a remote MCP HTTP server that responds to requests from more than just me. Or to make the entire chat server (with pre-configured remote MCP servers) accessible to a wider (company internal) audience.
I personally don’t think of MCP servers as having more utility than local services that individuals use with a local Claude/ChatGPT/etc client. If you are only using local resources, then MCP is just extra overhead. If your LLM can call a REST service directly, it’s extra overhead.
Where I really see the benefit is when building hosted services or agents that users access remotely. Think more remote servers than local clients. Or something a company might use for a production service. For this use-case, MCP servers are great. I like having some set protocol that I can know my LLMs will be able to call correctly. I’m not able to monitor every chat (nor would I want to) to help users troubleshoot when the model didn’t call the external tool directly. I’m not a big fan of the protocol itself, but it’s nice to have some kind of standard.
The short answer: not everyone is using Claude locally. There are different requirements for hosted services.
(Note: I don’t have anything against Claude, but my $WORK only has agreements with Google and OpenAI for remote access to LLMs. $WORK also hosts a number of open models for strictly on-prem work. That’s what guided my choices…)