MCP Ecosystem & Specification - The Model Context Protocol (MCP) ecosystem is still in its early stages, with significant room for growth and development [2][3] - The industry emphasizes the importance of adopting the full MCP specification to unlock rich, stateful interactions between agents [9] - The industry acknowledges a gap in MCP implementation, with a tendency to treat it as just another API wrapper [5] - Technical barriers, including missing support in clients, SDKs, documentation, and references, contribute to the limited adoption of the full MCP spec [6] - The industry highlights the need for developers to stay updated with the latest MCP specification and provide feedback on draft features [29] Tools & Dynamic Discovery - Tools are the most immediately successful aspect of MCP, but overuse can lead to quality problems and AI confusion [7][11][12] - Dynamic tool discovery allows servers to provide context-aware tools, enhancing the user experience [16][17][18] - VS Code offers user controls like per-chat tool selection and user-defined tool sets to manage tool complexity [13][15] Resources & Sampling - Resources provide a semantic layer for exposing files and data to both the LLM and the user, enabling more dynamic and stateful interactions [19][20] - Sampling allows servers to request LLM completions from the client, enabling progressive enhancement and interesting functionalities [22][23][24] Developer Experience & Community - The industry recognizes the need for improved developer experience when working on MCP servers, including debugging and logging [26] - VS Code offers a dev mode with debugging capabilities for MCP servers, simplifying the development process [26][27][28] - A community registry is being developed to facilitate the discovery of MCP servers [32]