Leveraging MCP at Scale: A Case Study from Anthropic

Unlocking the Power of MCP: How Standardizing on Message Passing Can Revolutionize Your Organization's Integration Efforts

1. John has spent 20 years building large scale systems and is currently a member of technical staff at Anthropic, focusing on tool calling and integration.
2. Models only recently became good at calling tools, leading to a surge in excitement and rapid development of various services and custom endpoints.
3. The initial euphoria led to integration chaos, as different services had their own ways of handling tool calling and authentication.
4. Over time, these endpoints started to resemble the MCP (Model Call Protocol) specification, which is a JSON RPC for sending messages between providers of context and models.
5. Anthropic decided to use MCP for everything involved in providing model context, standardizing on a single approach for engineers, making things faster and more efficient.
6. MCP solves problems that users might not have encountered yet, such as dealing with different billing models, token limits, and usage tracking in integrations.
7. Anthropic is seeing external remote MCP services emerging, which requires external network connectivity, authentication, and handling security concerns.
8. The company introduced the MCP gateway, a single point of entry for engineers to connect to MCP with a simple 'connect to MCP' call that returns an MCP SDK client session.
9. URL-based routing is used to route to external and internal servers, handling credential management automatically, providing a centralized place for rate limiting and observability.
10. Client libraries have been created to connect to the MCP gateway with a simplified process of passing a URL, org ID, and account ID (with signed token authentication).
11. The MCP SDK object allows new features to be added to the protocol and easily integrated by updating MCP packages internally.
12. The same code can seamlessly connect to internal and external integrations when it comes to transports, with various transport options available based on organizational needs.
13. Anthropic has set up a unified authentication model, handling OAuth at the gateway so that consumers don't have to worry about complexity in their apps.
14. Adding MCP support to new services is as simple as possible, with packages available for multiple languages and operational simplicity through standardized message formats.
15. Centralizing context for models provides a unified location for all the context that models are asking for and receiving, enabling better policy enforcement and content classification.
16. MCP prompt injection attacks and model access to sensitive data are potential risks that can be mitigated by centralizing context and enforcing policy.
17. Standardizing on something like MCP simplifies future development and allows organizations to focus on building features rather than plumbing infrastructure.
18. Building 'pits of success' makes the right way to do things the easiest way, encouraging developers to naturally follow best practices.
19. Centralizing shared problems at the appropriate layer enables teams to spend more time working on valuable and interesting business problems.
20. MCP is essentially JSON streams, with implementation details being a minor concern; choosing something like MCP simplifies development for future selves.
21. Anthropic encourages the audience to consider using MCP or another standard in their organizations, focusing on building pits of success and solving shared problems once for greater efficiency.

Source: AI Engineer via YouTube

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