What is MCP (Model Context Protocol)?

MCP (Model Context Protocol) is an open standard, created by Anthropic, that lets AI applications like Claude connect to external tools and data sources in a structured, secure way. Think of it as a common language: instead of every AI assistant needing a custom, one-off integration for every app it talks to, MCP gives developers one consistent format for exposing an app's data and actions to an AI agent. The AI can then read information from that app and, where permitted, take actions in it — but strictly within the boundaries the user has explicitly granted. MCP itself is not specific to trading or to Pluang; it's a general-purpose connector standard already used across many kinds of software. Pluang built its Agentic Trading integration on top of MCP, so an AI agent such as Claude connects to a user's Pluang account under this same permissioned model.

Before protocols like MCP existed, connecting an AI assistant to an external app typically meant custom-building a one-off integration for each app-AI pairing — brittle, hard to secure, and hard to maintain. MCP solves this with a standardized structure that any compliant AI application can speak:

• Servers — an app (like Pluang) exposes specific data and actions (e.g. "get portfolio holdings," "place a buy order") as MCP "tools," following the protocol's shared format
• Clients — an AI application (like Claude) that understands MCP can discover and call those tools once the user connects the two
• Permissions — the user decides what the AI agent is allowed to see and do; the agent cannot exceed what's been granted, and the app — not the AI model — enforces those boundaries
• Portability — because it's an open standard, any MCP-compliant AI client can, in principle, connect to any MCP-compliant app, without a custom integration for each pairing

On Pluang specifically, MCP is the mechanism underneath Pluang Agentic Trading: it defines how a connected AI agent can check a user's portfolio holdings, look up current US Stocks and Crypto prices, view transaction history, place buy/sell orders, and run backtests — all through natural-language instructions, and all within the permissions the user has set. For the product-level explanation of what Pluang Agentic Trading itself lets you do, see "What is Agentic Trading on Pluang?" For how this differs from a simple automated trading bot, see "What's the difference between an AI agent and a trading bot?"

Related questions:

Q: Did Pluang create MCP?
No. MCP (Model Context Protocol) was created by Anthropic as an open standard, not by Pluang. Pluang adopted MCP to build Agentic Trading, using it as the underlying connection layer between a user's Pluang account and a compatible AI agent such as Claude. Being an open standard means MCP's specification isn't proprietary to any single company — Pluang implemented its own MCP server to expose specific Pluang account data and actions, following that shared specification, rather than inventing its own private protocol.

Q: Is MCP the same thing as Pluang Agentic Trading?
No. MCP is the general underlying connection standard; Pluang Agentic Trading is Pluang's specific product built on top of it. MCP alone doesn't know anything about portfolios, stocks, or crypto — it's a generic way for an AI application to connect to any external tool or data source. Pluang Agentic Trading is what happens when Pluang implements MCP specifically for its own platform, defining the exact actions (checking balances, placing trades, running backtests) a connected AI agent can perform on a user's account.

Q: Do I need to understand MCP to use Pluang Agentic Trading?
No. MCP is the technical standard working behind the scenes; using Pluang Agentic Trading itself is meant to feel like a natural-language conversation with your AI agent about your Pluang account. You don't need to configure MCP servers or understand its technical structure yourself — that complexity is handled by Pluang and by the AI application you're using. Understanding MCP is useful background if you're curious how the connection works or how your permissions are technically enforced, but it isn't required to place a trade or check a price through your agent.

Q: Can any AI assistant use MCP to connect to Pluang?
Only AI applications that support the MCP standard can connect — you can use any AI platform that supports connecting to Agentic Trading, including but not limited to Claude, ChatGPT, and Gemini. Even for a supported client, the connection only works once the user explicitly links their Pluang account to it — MCP defines the connection format, not automatic access.

Q: Is connecting to Pluang via MCP secure?
MCP itself is designed around explicit, scoped permissions rather than handing an AI agent broad account access — the user grants access to specific data and actions, and the app enforces those boundaries on its end. Trades placed through a connected agent go through the exact same licensed entities and asset protections as trades placed manually in the app.