What is MCP?

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Overview

The Model Context Protocol (MCP) is an open, vendor-neutral spec that lets any AI agent call any tool or data source through a uniform JSON/HTTP interface—think USB-C for AI. By standardising the handshake, auth, and invocation format, MCP removes the bespoke glue code that normally couples each model to every integration. Today the protocol is already baked into OpenAI’s Responses API, Microsoft Copilot Studio, Google Gemini CLI, and dozens of third-party servers listed in Anthropic’s directory. ContexaAI sits on top of this ecosystem, giving you a one-click way to create, deploy, and compose MCP servers so your agents can focus on reasoning, not plumbing.

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What exactly is MCP?

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Definition & spec

MCP is a JSON-RPC–style protocol that defines:

• Handshake – the client announces supported schema versions & authentication; the server returns its tool manifest (functions, arguments, docs). (Links)
• Roots – optional scoped access boundaries that tell a server which files, databases or tenants it may touch.
• Invocation – a single /invoke endpoint where the client calls a tool with structured arguments and receives a typed response or stream.
• Auth & consent – layered around OAuth 2 / JWT plus an optional consent step so users can selectively grant tools.

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Why you should care

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How it works (architecture)

1. AI agent client (e.g., OpenAI Responses) starts a handshake with the MCP server announcing schema & auth.
2. Server replies with a tool manifest—each tool has name, description, parameters, and optional auth requirements.
3. Client calls /invoke with tool name + JSON args.
4. Server executes underlying integration (Slack API, GitHub REST, database query) and streams the result back.
5. Optional roots limit what the server can access, enforcing least-privilege.

ContexaAI generates the manifest, bundle tools, handle auth, and host the server so you only point your agent at a single URL.

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ContexaAI + MCP

With ContexaAI you can: