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One decision many enterprises have to make when implementing AI use cases revolves around connecting their data sources to the models they’re using.
Different frameworks like LangChain exist to integrate databases, but developers must write code whenever they connect models to a new data source. Anthropic hopes to change that paradigm by releasing what it hopes to be a standard in data integration.
Anthropic released its Model Context Protocol (MCP) as an open-source tool to provide users with a standard way of connecting data sources to AI use cases. In a blog post, Anthropic said the protocol will serve as a “universal, open standard” to connect AI systems to data sources. The idea is that MCP allows models like Claude to query databases directly.
Alex Albert, head of Claude Relations at Anthropic, said on X that the company’s goal is “to build a world where AI connects to any data source” with MCP as a “universal translator.”
“Part of what makes MCP powerful is that it handles both local resources (your databases, files, services) and remote ones (APIs like Slack or GitHub’s) through the same protocol,” Albert said.
A standard way of integrating data sources not only makes it easier for developers to point large language models (LLMs) directly to information but also eases data retrieval issues for enterprises building AI agents.
Since MCP is an open-source project, the company said it encourages users to contribute to its repository of connectors and implementations.
A standard for data integration
No standard way of connecting data sources to models exists just yet; this decision is left to enterprise users and model and database providers. Developers tend to write a specific Python code or a LangChain instance to point LLMs to databases. With each LLM functioning a little differently from each other, developers need a separate code for each one to connect to specific data sources. This often results in different models calling to the same databases without the ability to work together seamlessly.
Other companies extend their databases to make creating vector embeddings that can connect to LLMs easier. One such example is Microsoft integrating its Azure SQL to Fabric. Smaller firms like Fastn also offer a different method to connect data sources.
Anthropic, though, wants MCP to work even beyond Claude as a step toward model and data source interoperability.
“MCP is an open standard that enables developers to build secure, two-way co …