Introducing the Model Context Protocol

Takeaways

MCP (Anthropic, open standard) connects AI assistants to data sources — repos, business tools, dev environments — via a universal protocol instead of bespoke integrations per source.
Architecture: MCP servers expose data; MCP clients (AI apps) connect — secure, two-way connections at scale.
Launch included spec + SDKs, Claude Desktop local server support, and open-source pre-built servers (Google Drive, Slack, GitHub, Git, Postgres, Puppeteer).
Addresses model isolation behind silos — every new data source no longer requires a custom one-off implementation.
Early adopters: Block, Apollo; dev tools (Zed, Replit, Codeium, Sourcegraph) integrating for richer coding context.
Claude 3.5 Sonnet can rapidly scaffold MCP server implementations for org-specific datasets.

Foundational protocol for this vault’s MCP setup (QMD, Raindrop) — the plumbing layer ObsidianOS assumes when skills say “agent-agnostic MCP client.”

Which additional MCP servers (Gmail beyond gws CLI, Calendar) would most reduce ObsidianOS skill friction?