Glossary
MCP (Model Context Protocol)
An open standard introduced by Anthropic in late 2024 for connecting AI agents to external tools and data sources via a uniform protocol — like a "USB-C for AI agents."
Model Context Protocol (MCP) is an open standard introduced by Anthropic in November 2024 that defines a uniform way for AI agents to discover and interact with external tools, data sources, and services.
The problem MCP solves: before MCP, every AI agent integration was custom-coded. To give Claude access to your Notion workspace, you wrote bespoke integration code. To give it access to Slack, another integration. To give it access to your internal database, another. Every new agent + every new tool meant new integration work.
MCP defines a standard server-side protocol so that any agent (Claude, GPT, Gemini, custom) can discover and use any MCP-compliant tool without bespoke integration code. Tools advertise what they can do; agents discover and invoke.
Adoption as of 2026: most major AI tooling platforms now ship MCP servers. The ecosystem has grown to include MCP servers for GitHub, Linear, Notion, Slack, Stripe, Postgres, Supabase, AWS, GCP, and most other major SaaS + infrastructure providers. Custom MCP servers for internal tools are becoming a standard part of enterprise AI deployments.
Why it matters for automation: MCP dramatically reduces the integration burden for building agents. What used to take days of integration code now takes hours of MCP server configuration.
Example
A company builds a customer support agent in 2024. To give it access to their CRM, support tool, knowledge base, and internal product database, they write four custom integrations — about 2 weeks of engineering work. The same agent built in 2026 uses MCP servers for each system. Engineering work: about a day.
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