MCP (Model Context Protocol)

MCP is an open standard from Anthropic for connecting AI models to external tools, data sources, and applications through a consistent client-server protocol.

Model Context Protocol is the open standard, introduced by Anthropic in late 2024, that defines how LLM-based applications connect to external tools and data sources. Think of it as USB for AI — instead of every tool author re-inventing how their plugin talks to Claude/Cursor/ChatGPT, MCP defines one protocol everyone implements.

The architecture is straightforward:

MCP server — a small process that exposes a set of tools, resources, and prompts. Examples: a GitHub MCP server exposes create_pr, list_issues, etc.; a Postgres MCP server exposes query; a filesystem MCP server exposes read_file, write_file.
MCP client — the LLM-powered app (Claude Desktop, Cursor, Claude Code, an agent) that connects to MCP servers and exposes their tools to the model.
Transport — stdio for local, HTTP/SSE for remote.

Why this matters: before MCP, every AI app integrated tools its own way. Slack-for-ChatGPT, Slack-for-Claude, and Slack-for-Cursor were three separate integrations. With MCP, a single slack-mcp server works with all of them.

In 2025-2026, MCP has become the dominant integration pattern for AI dev tools. Major platforms — GitHub, Postgres, Linear, Notion, Figma, AWS, Vercel — ship official MCP servers. There are now thousands of community servers covering every major SaaS API.

For builders, MCP is the answer to "how do I let users connect their stack to my AI product?" Don't build a custom plugin system; ship an MCP client and let users plug in whichever MCP servers they want.

Related on ToolMango

Cursor

The AI-first code editor.

Claude

Anthropic's long-context AI for serious writing and reasoning.

FAQ

Is MCP only for Claude?

No. MCP is an open spec — Anthropic created it but it's vendor-neutral. Cursor, Continue, Cline, ChatGPT (via desktop apps), and many open-source agent frameworks all support MCP.

How is MCP different from OpenAI function calling?

Function calling is *how* a model invokes a tool. MCP is *how* a tool advertises itself to be invoked. They're complementary: an MCP server exposes functions; the model uses function calling to invoke them.

Related terms

AI agent — An AI agent is an LLM-driven system that takes actions in the world — calling tools, browsing, writing code, finishing tasks — instead of just answering questions.
LLM (Large Language Model) — A Large Language Model is a neural network trained on huge volumes of text to predict the next token, which produces emergent capabilities like reasoning, code generation, and translation.

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