TLDR:
The Model Context Protocol (MCP) is an open standard introduced by Anthropic in November 2024 that standardizes how AI systems—particularly LLMs and AI agents—integrate with external tools, systems, and data sources. As of 2026, MCP is the de facto standard supported by OpenAI, Google, Microsoft, AWS and the broader ecosystem.
How MCP Works
MCP defines a client-server protocol with stabilized terminology: server (exposes capabilities), client (consumes them), transport (the communication layer), primitives (tools, resources, prompts, sampling), and sampling (model invocation from server side). An MCP server might wrap a GitHub repo, a Postgres database, a Slack workspace, or a custom API—exposing them as tools the AI can invoke. Major SaaS platforms (GitHub, Slack, Google Drive, Notion, Jira, Salesforce) now ship official MCP servers.
MCP vs. A2A
MCP and A2A are complementary protocols: MCP connects an AI model to tools and data sources (“gives the agent its hands”); A2A (Agent-to-Agent, introduced by Google in April 2025) connects agents to each other for cross-team delegation. Together they form the infrastructure layer for multi-agent enterprise architectures.
Governance and Adoption
In December 2025, Anthropic donated MCP to the Agentic AI Foundation (AAIF), a directed fund under the Linux Foundation co-founded with Block and OpenAI. By March 2026, MCP surpassed 97M monthly SDK downloads and 81K GitHub stars. For founders building AI products, MCP support has become a baseline expectation: deployment time for tool integrations dropped from days to minutes after migrating to MCP-native architecture in benchmarked deployments.