An open standard that lets AI models connect to tools and data sources through one consistent interface.
Official siteThe Model Context Protocol (MCP) is an open standard, introduced by Anthropic in late 2024, for connecting AI models and agents to external tools, data and systems. It plays a role often described as "USB-C for AI": instead of writing a bespoke integration for every model-to-system pairing, you expose capabilities once as an MCP server and any MCP-compatible client can use them.
An MCP server advertises tools (actions the model can call), resources (data it can read) and prompts. This decouples what a model can do from how it is wired up, and it has been adopted across the major AI ecosystems, making it a practical backbone for real agent work.
MCP defines a client-server protocol between an AI application (the client) and capability providers (servers). A server exposes tools, resources and prompts over a standard transport; the model discovers and invokes them without knowing the implementation details behind each one.
When we build AI agents that must act on real systems — query a database, call an internal API, read documents — MCP lets us expose those capabilities once and reuse them across agents and models, instead of hard-wiring each integration.
MCP is young, so tooling and conventions are still settling and the security model (what an agent is allowed to invoke) demands careful design. For a single throwaway integration, a direct API call is simpler. The standard pays off once you have several tools and want them portable across agents.
Our AI/agent work uses TypeScript and Node to build MCP servers that expose internal tools and data to agents in a controlled, reusable way — the same pattern behind our RAG knowledge assistants, where retrieval is exposed as an MCP capability.
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Common questions
Straight answers on how this fits your marketing and build.
It removes the M-times-N integration explosion between AI models and the systems they need to use. Expose a capability once as an MCP server and any MCP-compatible client can call it, instead of writing a custom connector for every model-and-tool pair.
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