The other day I was looking at the release notes for the recently published release 1.8 of NumPy, the library that is the basis for most of the Scientific Python ecosystem. As usual, it contains a list of new features and improvements, but also sections such as "dropped support" (for Python 2.4 and 2.5) and "future changes", to be understood as "incompatible changes that you should start to prepare for". Dropping support for old Python releases is understandable: maintaining compatibility and testing it is work that needs to be done by someone, and manpower is notoriously scarce for projects such as NumPy. Many of the announced changes are in the same category: they permit removing old code and thus reduce maintenance effort. Other announced changes have the goal of improving the API, and I suppose they were more controversial than the others, as it is rarely obvious that one API is better than another one.
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Explosive MCP Adoption in 2 Years
Den Delimarsky, lead maintainer of the Model Context Protocol and Claude Code engineer at Anthropic, delivers a keynote on MCP's two-year journey from a basic protocol with two SDKs to the industry standard powering half a billion downloads per month. - **MCP's Origin Story** - Launched in November 2024 with a spec, two transports (STDIO and HTTP), two SDKs (Python and TypeScript), and a handful of clients including Claude Desktop - **Five Spec Releases** - Every revision was driven by community input, improving security, adding OAuth support, and simplifying the developer experience for building MCP clients and servers - **The March 2025 Inflection Point** - A 14-day window when major industry players publicly backed MCP, signaling enterprise adoption beyond the early enthusiast community - **MCP 2.0 Release** - The biggest spec update since launch, removing sessions for stateless deployment on AWS Lambda and Cloudflare Workers, and introducing the extensions framework - **Extensions Framework** - MCP Apps, Tasks, and Enterprise managed apps can now be tested as extensions before being added to the core specification - **Explosive Growth** - SDK downloads grew 13x year-over-year, reaching 500 million per month and 3.06 billion cumulative across Python, TypeScript, and C# alone - **Registry Scale** - The open-source MCP server registry surpassed 20,000 entries, a 45x increase since its September launch - **10 Official SDKs** - From the original two, MCP now supports Go (Google), C# (Microsoft), Kotlin (JetBrains), Swift, Rust, and more, each sponsored by major platform companies - **Community Momentum** - 184,000 GitHub stars, 2,500+ unique committers, 736 PRs merged and 600+ issues solved last month alone Whether you are building your first MCP server or scaling agent infrastructure across your organization, this keynote lays out exactly where the protocol stands and where it is heading. Links and Resources - MCP Specification: https://spec.modelcontextprotocol.io - MCP Blog: https://blog.modelcontextprotocol.io - MCP GitHub: https://github.com/modelcontextprotocol - Agentic AI Foundation: https://agenticaifoundation.org - Anthropic: https://www.anthropic.com Timestamps (approximate - adjust as needed) 00:00 Introduction 01:04 Two years of MCP: the origin story 02:43 MCP in 2024: the early days 03:40 Five spec releases in under two years 04:42 The 14 days that changed MCP adoption 05:39 MCP 2.0: the biggest release since launch 06:37 The extensions framework 07:04 MCP as enterprise agentic substrate 08:06 SDK download growth and registry scale 09:51 GitHub ecosystem metrics 11:04 From 2 SDKs to 10 11:55 Community momentum and contribution stats 12:16 Thank you to the MCP community #ModelContextProtocol #AgenticAI #MCPDevSummit
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