MCP is an open standard developed by Anthropic, designed to streamline how LLMs interact with external tools and data sources. Think of it as a "USB-C port" for AI applications, providing a standardized way to connect AI models to various peripherals and accessories
The technology enables developers to build secure, two-way connections between their data sources like business tools or software or even a database, and AI-powered tools. This architecture allows AI assistants to perform tasks such as creating GitHub repositories, querying databases, or retrieving documents from cloud storage.
This helps developers to build a seamless connection between data sources and AI applications like chatbots while also helping AI models generate better and more relevant responses.
Anthropic introduced MCP as an open-sourced project in November 2024.
Traditionally, AI interactions were limited to isolated exchanges, lacking memory of previous conversations or user preferences.
MCP addresses this by allowing AI models to receive a "context packet" containing user profiles, task intents, interaction histories, and specific constraints. This structured information empowers AI to deliver more personalized and coherent responses, akin to a human assistant who remembers past interactions and understands ongoing projects.
The protocol operates on a client-server architecture, where MCP clients (AI applications) communicate with MCP servers (external data sources or tools) using a JSON-RPC 2.0 protocol, supporting streaming responses and partial results.
This setup facilitates seamless integration, enabling AI to perform tasks like summarizing documents, managing schedules, or interfacing with software development tools without redundant coding efforts .
The standard is becoming mainstream due to the arrival of AI agents.
As developers build more AI agents that could tie up multiple tasks together, MCP could prove to be useful.
Introducing the Model Context Protocol (MCP)
An open standard we've been working on at Anthropic that solves a core challenge with LLM apps - connecting them to your data.
No more building custom integrations for every data source. MCP provides one protocol to connect them all: pic.twitter.com/kYsivQyPDq— Alex Albert (@alexalbert__) November 25, 2024
In essence, MCP is able to revolutionize the way AI systems interact with external data and tools, by providing a standardized, open protocol, where LLMs can access and utilize relevant context, transforming AI from a reactive tool into a proactive collaborator.
When Anthropic releases MCP, it shared pre-built MCP servers for popular enterprise systems like Google Drive, Slack, GitHub, Git, Postgres, and Puppeteer.
Soon, enterprises and companies started adopting the technology, integrating it into IDEs like Zed and platforms like Replit to provide coding assistants with real-time context.
Enterprise assistants used by companies such as Block and Apollo to allow internal assistants to access proprietary documents and CRM systems.
Applications like AI2SQL utilize MCP to connect models with SQL databases, enabling plain-language queries.
Anthropic rival OpenAI also said the company would be adopting MCP across their products.
The company said that MCP is now integrated with OpenAI Agents SDK, allowing developers to connect their MCP servers directly to agents. OpenAI is also working on bringing MCP support to the OpenAI API and the ChatGPT desktop app, with more updates coming up.
MCP OpenAI Agents SDK
You can now connect your Model Context Protocol servers to Agents: https://t.co/6jvLt10Qh7
We’re also working on MCP support for the OpenAI API and ChatGPT desktop app—we’ll share some more news in the coming months.— OpenAI Developers (@OpenAIDevs) March 26, 2025
Amazon's AWS also joined the bandwagon, by offering MCP support across its platform, including on Bedrock Agents via the Inline Agents API, open-source MCP servers for code assistants, guides for running MCP infrastructure, and more.
This was announced by Swami Sivasubramanian, Head of AI Services and Data at AWS in a post on X.
Agentic systems offer possibilities that extend far beyond today’s chatbots and will drive innovations we can’t even anticipate. These autonomous systems will be transformational, but to reach their full potential, agents need the right data and tools and must be able to connect… pic.twitter.com/lGNVdr0Doo
— Swami Sivasubramanian (@SwamiSivasubram) April 1, 2025
Google’s CEO, Sundar Pichai, first teased it on on X, "To MCP or not to MCP, that’s the question."
To MCP or not to MCP, that's the question. Lmk in comments
— Sundar Pichai (@sundarpichai) March 30, 2025
Then, Google DeepMind said that the company is adding support for MCP, with CEO Demis Hassabis making the announcement on X saying that MCP was quickly becoming accepted as a common protocol with AI agents around.
"MCP is a good protocol and it’s rapidly becoming an open standard for the AI agentic era," wrote Hassabis.
"Look forward to developing it further with the MCP team and others in the industry."
MCP is a good protocol and it's rapidly becoming an open standard for the AI agentic era. We're excited to announce that we'll be supporting it for our Gemini models and SDK. Look forward to developing it further with the MCP team and others in the industry https://t.co/RAJH8J5zbB
— Demis Hassabis (@demishassabis) April 9, 2025
Similarly, Cloudflare has also announced its support for MCP by partnering with identity providers Auth0 and Stytch. This collaboration simplifies the process for developers to delegate permissions to AI agents, streamlining secure agent deployment.
By integrating with Auth0 and Stytch, Cloudflare enables developers to add robust authentication and authorization to remote MCP servers built on Cloudflare Workers. This setup allows AI agents to securely access external services on behalf of users, facilitating tasks such as sending emails, booking meetings, or deploying code changes.
