How Claude, ChatGPT, and Gemini each built MCP differently

Zehra Nur — Fri, 10 Jul 2026 12:50:24 +0000

The Model Context Protocol settled its place as a standard by now. What's more interesting for anyone building on top of it is how differently the three big vendors implemented the same spec, because those choices decide what you can actually ship.

What MCP standardized

MCP defines how a model talks to external tools and data through a server that exposes tools, resources, and prompts over a defined transport. Before it, every integration was bespoke client code. After it, a tool author writes one server and any MCP client can call it.

The adoption curve backs this up. Monthly SDK downloads across the Python and TypeScript SDKs went from around 2 million at launch (November 2024) to over 97 million by March 2026. The public server count passed 10,000. In December 2025 Anthropic donated the protocol to the Agentic AI Foundation under the Linux Foundation, with OpenAI, Google, Microsoft, and AWS backing it, which is what turned it from an Anthropic project into a neutral standard.

So the spec is shared. The implementations are not. Here's where they diverge.

Claude: local-first, servers on your machine

Anthropic treats MCP as part of Claude's native agentic loop. The servers run locally, in the desktop app or the terminal, over stdio. That means direct access to local folders, your running dev environment, and databases on your machine with no network hop in between.

Tradeoffs for a developer:

Full local access and the most complete protocol support, since Anthropic authors the spec.
Custom, non-catalog servers still mean editing JSON config by hand. That's fine for developers and rough for everyone else.
The official Connectors Directory reached 439 entries by June 2026 for the one-click path, but the power is in wiring your own.
MCP Apps (January 2026) added interactive UI previews pulled from tools like Figma and Slack into the chat surface.

If you're building developer tooling, this is the most flexible target.

ChatGPT: remote-only, rendered as apps

OpenAI went the opposite direction on transport. ChatGPT supports remote MCP servers only, reached over streamable HTTP. No local servers, no stdio.

What that buys and costs:

Zero client-side setup for the end user. They enable your tool in settings and it works. No install step.
You cannot run a local dev-style server the way you can with Claude or Cursor. Your server has to be hosted.
The Apps SDK extends MCP so tool output renders as inline interactive widgets: cards, charts, forms, data tables, shown in an iframe inside the conversation.
The App Directory opened to third-party submissions in December 2025 and passed 60 apps in early 2026.

This is the target if you want a consumer-facing tool that feels native to the chat, not a config screen.

Gemini: MCP behind Google Cloud governance

Google's implementation wraps MCP in enterprise infrastructure. The path runs from an enterprise data lake such as BigQuery, through Google Cloud IAM for permissions, into a centralized and audited MCP server, then to the model.

For a developer or platform team:

Access goes through the Gemini CLI for local work and a fully managed remote MCP server for the Gemini Enterprise Agent Platform, launched June 30 2026.
Google positions itself as the governed intermediary, so data stays inside its cloud boundary and audit trail even when a workflow routes to other models.
Responses are structured rather than rendered as interactive UI. No iframe widgets yet.
Google reported more than 50 managed MCP servers, with a cap of 100 enabled actions per custom server.

This is the target when governance and data residency matter more than UI polish.

Why the differences matter

The transport choice alone (local stdio vs remote HTTP) decides whether you can build a local dev tool or a hosted consumer app. The rendering choice (raw structured output vs interactive iframe widgets) decides whether your tool feels like a function call or a product. The governance choice decides whether an enterprise security team will let it near their data.

MCP made the connection layer a solved problem. That pushed the real competition up a level, to the experience built on top. Whichever platform you target, you're not choosing a protocol anymore. You're choosing a philosophy about where code runs, who renders the UI, and who holds the data.

Figures are the most recent public numbers as of mid-2026 and use different counting methods per vendor (a curated connector directory, an app store, a managed-server count), so read them as scale, not a like-for-like scoreboard.

Hacktoberfest 2023 Pledge

Zehra Nur — Mon, 09 Oct 2023 14:52:27 +0000

My Pledge

I, Zehra, pledge to participate in Hacktoberfest 2023 to the best of my ability. My aim is to contribute meaningfully to the open-source community through my skills and efforts.

Objectives

To submit at least four pull requests to open-source repositories during the month of October 2023.
To improve the quality of projects by providing valuable code changes, documentation updates, or other types of contributions.
To adhere to the community standards and guidelines set by the maintainers of the projects to which I contribute.

Guidelines I Will Follow

I will read the contributing guidelines of each repository to which I contribute and follow them diligently.
I will be respectful and courteous in my interactions with other community members.
I will ensure that my contributions are meaningful and add value to the project.

Rewards

While I understand that the reward of participating in Hacktoberfest lies in the learning and the joy of contributing to open-source, I also acknowledge the additional incentives of swag and recognition provided by DigitalOcean and other sponsors.

Conclusion

Through my participation in Hacktoberfest 2023, I aim to be a proactive and beneficial member of the open-source community. I look forward to contributing to projects that excite me and learning from the experiences of others.

DEV Community: Zehra Nur