WebMCP vs Anthropic MCP: Understanding the Two Protocols
Two Protocols, One Vision
Despite sharing the "MCP" name, WebMCP and Anthropic's Model Context Protocol are architecturally distinct systems designed for different layers of the AI agent stack. Understanding their differences and complementary strengths is essential for any team building AI-integrated products.
Architecture Comparison
Anthropic MCP: Server-Side First
Anthropic's MCP is a JSON-RPC based protocol that runs over stdio or HTTP. MCP servers are backend processes (typically Python or Node.js) that expose tools, resources, and prompts to AI clients. Authentication is handled through OAuth 2.1 with separate credential management.
The protocol supports three primitive types: tools (callable functions), resources (data endpoints), and prompts (templated instructions). This makes it a comprehensive integration layer for backend services.
WebMCP: Browser-Native
WebMCP runs entirely in the browser tab. Tools are registered through the navigator.modelContext JavaScript API and executed within the page's existing security context. There is no separate server process — the website itself becomes the tool provider.
Currently, WebMCP supports tools only (no resources or prompts), keeping the API surface small and focused.
Transport Layer
| Aspect | Anthropic MCP | WebMCP |
|---|---|---|
| Protocol | JSON-RPC 2.0 | Browser postMessage |
| Transport | stdio, HTTP/SSE | In-process (same tab) |
| Latency | Network round-trip | Near-zero (in-process) |
| Serialization | JSON | Structured clone |
Authentication Model
This is perhaps the most significant practical difference:
Anthropic MCP requires separate credential management. Each MCP server connection needs its own OAuth 2.1 flow, API keys, or other authentication mechanism. This adds complexity but provides fine-grained access control.
WebMCP inherits the browser session. If a user is logged into a website, WebMCP tools execute with that same authenticated context. No separate auth flow is needed. This dramatically simplifies integration but means tool access is tied to the user's browser session state.
When to Use Each
Use Anthropic MCP When:
- Building server-side integrations (databases, APIs, file systems)
- The AI agent operates outside a browser context
- You need resources and prompts, not just tools
- Fine-grained, per-service authentication is required
- Building multi-client ecosystems where various AI providers connect
Use WebMCP When:
- The AI agent interacts with your website through a browser
- You want to leverage existing user authentication
- Client-side JavaScript can handle the tool logic
- You want zero-infrastructure tool exposure
- User workflows involve forms, UI interactions, or visual confirmation
Use Both When:
- Your product has both a web interface and an API
- Browser-based agents need client-side tools while CLI/desktop agents need server-side tools
- You want maximum AI agent compatibility across all contexts
Governance
Anthropic donated MCP to the Linux Foundation's AI & Data Foundation (AAIF) in late 2025, creating a vendor-neutral governance model. WebMCP is being developed under the W3C Web Machine Learning Community Group, co-led by Google and Microsoft engineers.
Both protocols are open-source and designed for broad ecosystem adoption, but their governance homes reflect their target domains: AAIF for cross-platform AI tooling, W3C for web standards.
The Convergence Thesis
Long-term, expect these protocols to develop interoperability bridges. The MCP-B project already provides transport layers that can connect WebMCP's browser-native tools with Anthropic MCP's server-side ecosystem. The vision is a unified tool landscape where an AI agent seamlessly discovers and invokes capabilities regardless of whether they live in a browser tab or on a backend server.