| November 28, 2024
Anthropic has introduced a new standard for connecting AI assistants to data systems. Called the Model Context Protocol (MCP), this open-source standard aims to help AI models deliver more accurate and contextually relevant responses by accessing data across various platforms.
What is MCP?
MCP enables AI models — not just Anthropic’s — to interact with data from business tools, software applications, content repositories, and development environments.
In a blog post, Anthropic described the problem MCP addresses:
“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.”
By implementing MCP, developers can establish two-way connections between data sources and AI applications, such as chatbots. This is achieved through MCP servers (to expose data) and MCP clients (apps and workflows that access the data).
For example, MCP allows an AI assistant to:
- Connect directly to GitHub
- Create a repository
- Open a pull request (PR)
Here’s a quick demo shared by Alex Albert:
“Watch Claude connect directly to GitHub, create a new repo, and make a PR through a simple MCP integration. Building this integration took less than an hour once MCP was set up in the Claude desktop app.”
Adoption and Ecosystem
Several companies, including Block and Apollo, have already integrated MCP into their systems. Developer tooling platforms such as Replit, Codeium, and Sourcegraph are also adding MCP support.
Anthropic claims MCP simplifies development by replacing fragmented integrations with a sustainable, standard protocol:
“Instead of maintaining separate connectors for each data source, developers can now build against a standard protocol.”
Developers can now begin building MCP connectors, and subscribers to Anthropic’s Claude Enterprise plan can use prebuilt MCP servers for platforms like Google Drive, Slack, and GitHub. The company also plans to release toolkits to support larger-scale deployments across organizations.
Challenges and Competition
MCP faces significant hurdles, especially from competitors like OpenAI. OpenAI recently introduced a data-connecting feature for ChatGPT called Work with Apps, which lets the chatbot interact with coding apps and plans to expand to other applications. Unlike Anthropic, OpenAI is partnering with select collaborators rather than open-sourcing its approach.
The efficacy of MCP also remains unproven. While Anthropic claims it improves context retrieval for tasks such as coding, it hasn’t yet provided benchmarks to substantiate these claims.
Anthropic remains optimistic about MCP’s potential, inviting developers to contribute to the open-source project. As stated in their blog post:
“We’re committed to building MCP as a collaborative ecosystem. We invite developers to help shape the future of context-aware AI.”
