Introducing the Model Context Protocol
The Model Context Protocol (MCP) is an open 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.
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Anthropic’s mode of operation has moved from catching up to leading OpenAI in shaping the industry ecosystem.
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.
Protocols shape the trajectory of technology and if MCP gets adopted (it looks reasonably well thought out on a first glance) at scale, it not only protects Anthropic and their investment from competing approaches, but significantly eases the integration of AI in enterprises by consolidating to a common standard.
This has to be seen in context of the increasingly tight integration of Anthropic products with their major investor Amazon, which, through AWS offer one of the largest API platforms on the planet, critically relying on and benefitting from standardized protocols.
Positive move for enterprises looking to adopt
Overall the move is broadly beneficial for consumers - it’s a real problem that needs solving and pressure for a non proprietary solution is important.
The incentive for large platforms with strong lock-in of their customers like Microsoft and Google is to have proprietary solutions that act as a moat against customers switching to different vendors and invalidating billions in incentive spend in form of free courses, compute credits and integration aid.
Enterprises however do not benefit from vendor lock-in at all in a highly competitive environment where “the best” solution and SOTA change several times a month and costs are dropping by order of magnitude.
Data and solutions portability is a key consideration for low risk AI adoption - and Anthropic, still the underdog but rapidly gaining market share on the lucrative API market, stands to benefit from portability for than incumbent.