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INTRODUCING THE MODEL CONTEXT PROTOCOL

25. Nov. 2024●3 min read

Today, we're open-sourcing the Model Context Protocol (MCP), a new standard for
connecting AI assistants to the systems where data lives, including content
repositories, business tools, and development environments. Its aim is to help
frontier models produce better, more relevant responses.

As AI assistants gain mainstream adoption, the industry has invested heavily in
model capabilities, achieving rapid advances in reasoning and quality. Yet 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 addresses this challenge. It provides a universal, open standard for
connecting AI systems with data sources, replacing fragmented integrations with
a single protocol. The result is a simpler, more reliable way to give AI systems
access to the data they need.


MODEL CONTEXT PROTOCOL

The Model Context Protocol is an open standard that enables developers to build
secure, two-way connections between their data sources and AI-powered tools. The
architecture is straightforward: developers can either expose their data through
MCP servers or build AI applications (MCP clients) that connect to these
servers.

Today, we're introducing three major components of the Model Context Protocol
for developers:

 * The Model Context Protocol specification and SDKs
 * Local MCP server support in the Claude Desktop apps
 * An open-source repository of MCP servers

Claude 3.5 Sonnet is adept at quickly building MCP server implementations,
making it easy for organizations and individuals to rapidly connect their most
important datasets with a range of AI-powered tools. To help developers start
exploring, we’re sharing pre-built MCP servers for popular enterprise systems
like Google Drive, Slack, GitHub, Git, Postgres, and Puppeteer.

Early adopters like Block and Apollo have integrated MCP into their systems,
while development tools companies including Zed, Replit, Codeium, and
Sourcegraph are working with MCP to enhance their platforms—enabling AI agents
to better retrieve relevant information to further understand the context around
a coding task and produce more nuanced and functional code with fewer attempts.

"At Block, open source is more than a development model—it’s the foundation of
our work and a commitment to creating technology that drives meaningful change
and serves as a public good for all,” said Dhanji R. Prasanna, Chief Technology
Officer at Block. “Open technologies like the Model Context Protocol are the
bridges that connect AI to real-world applications, ensuring innovation is
accessible, transparent, and rooted in collaboration. We are excited to partner
on a protocol and use it to build agentic systems, which remove the burden of
the mechanical so people can focus on the creative.”

Instead of maintaining separate connectors for each data source, developers can
now build against a standard protocol. As the ecosystem matures, AI systems will
maintain context as they move between different tools and datasets, replacing
today's fragmented integrations with a more sustainable architecture.


GETTING STARTED

Developers can start building and testing MCP connectors today. Existing Claude
for Work customers can begin testing MCP servers locally, connecting Claude to
internal systems and datasets. We'll soon provide developer toolkits for
deploying remote production MCP servers that can serve your entire Claude for
Work organization.

To start building:

 * Install pre-built MCP servers through the Claude Desktop app
 * Follow our quickstart guide to build your first MCP server
 * Contribute to our open-source repositories of connectors and implementations


AN OPEN COMMUNITY

We’re committed to building MCP as a collaborative, open-source project and
ecosystem, and we’re eager to hear your feedback. Whether you’re an AI tool
developer, an enterprise looking to leverage existing data, or an early adopter
exploring the frontier, we invite you to build the future of context-aware AI
together.





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