Source URL: https://simonwillison.net/2024/Nov/25/model-context-protocol/#atom-everything
Source: Simon Willison’s Weblog
Title: Introducing the Model Context Protocol
Feedly Summary: Introducing the Model Context Protocol
Interesting new initiative from Anthropic. The Model Context Protocol aims to provide a standard interface for LLMs to interact with other applications, allowing applications to expose tools, resources (contant that you might want to dump into your context) and parameterized prompts that can be used by the models.
Their first working version of this involves the Claude Desktop app (for macOS and Windows). You can now configure that app to run additional “servers" – processes that the app runs and then communicates with via JSON-RPC over standard input and standard output.
Each server can present a list of tools, resources and prompts to the model. The model can then make further calls to the server to request information or execute one of those tools.
(For full transparency: I got a preview of this last week, so I’ve had a few days to try it out.)
The best way to understand this all is to dig into the examples. There are 13 of these in the modelcontextprotocol/servers GitHub repository so far, some using the Typesscript SDK and some with the Python SDK (mcp on PyPI).
My favourite so far, unsurprisingly, is the sqlite one. This implements methods for Claude to execute read and write queries and create tables in a SQLite database file on your local computer.
This is clearly an early release: the process for enabling servers in Claude Desktop – which involves hand-editing a JSON configuration file – is pretty clunky, and currently the desktop app and running extra servers on your own machine is the only way to try this out.
The specification already describes the next step for this: an HTTP SSE protocol which will allow Claude (and any other software that implements the protocol) to communicate with external HTTP servers. Hopefully this means that MCP will come to the Claude web and mobile apps soon as well.
Via @alexalbert__
Tags: alex-albert, anthropic, sqlite, claude, ai, llms, python, generative-ai
AI Summary and Description: Yes
Summary: The Model Context Protocol by Anthropic introduces a standardized interface for Large Language Models (LLMs) to interact with various applications, significantly enhancing their capability to leverage external resources and execute tasks. This initiative stands to improve the usability of LLMs in applications by providing a structured way to integrate tools and information seamlessly.
Detailed Description:
The Model Context Protocol (MCP) developed by Anthropic presents an innovative approach for integrating Large Language Models (LLMs) with external applications. Below are the key components and implications of this initiative:
– **Standard Interface**: MCP aims to create a common framework for LLMs to communicate with other applications, enhancing interoperability.
– **Resource Interaction**: Applications can expose tools and resources, including contextual data needed by the models, which can improve the models’ efficiency and responsiveness.
– **Initial Implementation**: The first working version is integrated with the Claude Desktop app for both macOS and Windows, allowing users to run additional processes that communicate with the models through JSON-RPC.
– **Server Configuration**: Users can configure additional “servers” via a JSON configuration file, indicating a focus on customization and extensibility for developers.
– **Examples Available**: A range of examples (13 at present) is provided in the modelcontextprotocol/servers GitHub repository, showcasing different use cases, including functionalities using the SQLite database.
– **Future Enhancements**: Plans for an HTTP SSE protocol are in place, which aims to facilitate communication between Claude and external HTTP servers, potentially expanding the protocol’s application beyond the desktop environment.
This initiative is particularly relevant for professionals in security, compliance, and AI development, highlighting the need for robust interaction protocols that can also maintain security standards when integrating multiple systems.
Overall, the development of the Model Context Protocol represents a significant step in advancing LLM capabilities, emphasizing both utility and flexibility for developers seeking to enhance their applications with AI functionalities.