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What is the Model Context Protocol (MCP)?

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Even the most sophisticated models are constrained by their isolation from data, trapped behind information silos and legacy systems. Every new data source requires its own custom implementation, making truly connected systems difficult to scale...[MCP] provides a universal, open standard for connecting AI systems with data sources, replacing fragmented integrations with a single protocol.
— Anthropic/ AI Research Organization
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A visual representation of the MCP architecture, provided by modelcontextprotocol.io

The Model Context Protocol (MCP) is an open protocol introduced by Anthropic that standardizes how large language models (LLMs) interface with external tools, data sources, and services.

Instead of building custom integrations for every model or tool, MCP provides a shared framework that lets AI agents access capabilities like reading files, calling APIs, or using developer tools — all through structured primitives.

Why does MCP matter?

As AI agents grow more capable, they need secure, modular access to the real world: databases, APIs, user files, and even third-party SaaS apps. Without standards, each integration becomes bespoke and brittle.

MCP solves this with a few core primitives:

  • Resources — Data exposed to the model (e.g., file contents, databases)
  • Tools — Actions the model can take (e.g., “createPullRequest”, “sendEmail”)
  • Prompts — Instructional contexts or templates (e.g., how to use a tool)

These primitives are exposed over a JSON-RPC interface between MCP Clients (the AI model or its orchestrator) and MCP Servers (external tool wrappers).

Key Benefits:

  • Eliminates fragile custom integrations
  • Supports secure, permissioned access to tools
  • Enables composability: one model can access many tools with a shared protocol

Example Use Case:

In Anthropic's demo, Claude uses MCP to:

  1. Access a GitHub API wrapper tool
  2. Create a repo, add files, and open a pull request — all from a prompt

This allows seamless orchestration of multi-step tasks by AI agents.

FAQ

What is MCP - Model Context Protocol?
An open protocol that standardizes how language models interact with external tools, data, and prompts through structured primitives.
Who created MCP?
MCP was introduced by Anthropic in 2024 as part of their Claude ecosystem and released as an open standard.
How does MCP work?
It defines a client-server model where LLM clients request access to resources, tools, or prompts from an MCP server using JSON-RPC.
Why is MCP useful for developers?
It simplifies AI integration with apps and services by standardizing access to tools, avoiding one-off APIs or custom function call logic.
Is MCP open source?
Yes. MCP is open and available for implementation across different AI platforms. Anthropic provides reference SDKs in several languages.

Related Stuff

  • AI Agents: Autonomous systems that can act on your behalf using reasoning and tools
  • Function Calling: A way for models to trigger external actions
  • Tool Use in LLMs: Why and how language models use APIs and plugins
  • JSON-RPC: A lightweight protocol used for remote procedure calls, used by MCP

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