WebMCP vs MCP: What's the Difference?
Both have "MCP" in the name. Both connect AI models to tools. But they operate at completely different layers and solve different problems. Here's a clear breakdown.
The short answer
MCP
Model Context Protocol
A server-side protocol by Anthropic. Lets AI models connect to external tools, databases, and services via a running server process.
Use when: building developer tools, IDE integrations, data connectors.
WebMCP
Web Model Context Protocol
A browser-native API standard by Google. Lets websites expose structured tools directly to AI agents visiting the page in a browser.
Use when: making a public website actionable by AI agents.
MCP: connecting AI to services
MCP (Model Context Protocol) was introduced by Anthropic in late 2024. It defines a standard way for AI models — primarily Claude — to connect to external tools and data sources via a server process running on your machine or network.
The canonical MCP use case is a developer running a local server that gives Claude access to their filesystem, their database, or their company's internal APIs. You've probably seen this if you've used Claude Code — it connects to your local environment via MCP servers.
MCP is server-side, opt-in, and most commonly used by developers building AI-connected tooling. It does not run in the browser and has no awareness of web pages.
WebMCP: connecting AI to websites
WebMCP was proposed by Google and is being standardised for the browser. It adds a navigator.modelContext API that any webpage can use to register named tools with descriptions and input schemas.
When an AI agent visits a page, it queries navigator.modelContext.tools and discovers what actions are available — then calls them with structured arguments. No server on your end, no configuration on the AI's end beyond WebMCP support.
WebMCP is designed for public websites. The target audience is not developers building AI services — it's developers and site owners who want their existing websites to work reliably with AI agents.
Side-by-side comparison
| Aspect | MCP | WebMCP |
|---|---|---|
| Layer | Server-side (runs a separate process) | Browser-side (runs in the page) |
| Who exposes tools | Developers building AI-connected services | Website owners exposing page actions |
| Discovery | AI connects to a known server endpoint | AI queries navigator.modelContext on the page |
| Requires backend? | Yes — runs a server process | No — one script tag, no server changes |
| Use case | IDE plugins, data connectors, local tools | E-commerce, SaaS, any public website |
| Standardised by | Anthropic | Google / W3C proposal |
| Browser required? | No | Yes — runs in a real browser session |
They're complementary, not competing
A common misconception is that WebMCP replaces MCP or vice versa. They don't overlap — they operate at completely different layers.
Imagine an AI assistant helping a user shop online. The AI might use MCP to connect to the user's personal data (order history, preferences) stored in a local service — and then use WebMCP to interact with the retailer's website (search products, add to cart, apply coupon).
MCP is the AI's connection to its own tools and data. WebMCP is the AI's connection to the websites it visits.
Which one do you need?
Use MCP if you're building a developer tool or internal service
You're creating a Claude integration, building an IDE plugin, or connecting internal data to an LLM. MCP is the right protocol — it's well-supported by Claude and growing across other models.
Use WebMCP if you own a website and want AI agents to interact with it
You run an e-commerce store, SaaS product, or any public site and you want AI assistants to be able to search it, add items to cart, or submit forms on behalf of users. WebMCP via Aigentably is what you want — no backend required.
Add WebMCP to your site
One script tag. No backend. AI agents can start calling your tools in minutes.
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