The Future of MCPs
a year ago
- #AI
- #LLMs
- #MCPs
- MCPs (Model Context Protocols) are standardized APIs that connect external data sources or applications to large language models (LLMs) like ChatGPT or Claude.
- MCPs enable LLMs to access real-time data, take actions on the web, and function more like agents than static chatbots.
- Two main types of MCP Servers exist: developer-focused tools (e.g., Cursor, Claude Code) and web/action-oriented tools for real-world tasks (e.g., booking events, sending emails).
- The author built two experimental MCP servers: GPT Learner (a developer tool) and a prediction market MCP connected to betsee.xyz.
- Current limitations of MCPs include rough user experience, lack of broad client support, security risks, and manual installation processes.
- MCP clients (e.g., ChatGPT, Claude) hold significant power, controlling which tools users see and how responses are surfaced.
- MCPs are expected to evolve into a framework resembling a combination of search engines and mobile app stores, with major LLM providers acting as gatekeepers.
- Future opportunities include MCP wrapper/server packs, affiliate shopping engines, MCP-first content apps, and enterprise private MCP solutions.
- Specialized MCP clients tailored to specific industries (e.g., travel, HR) are likely to emerge.
- The author predicts that most users will rely on default AI experiences with pre-installed MCPs, while power users may opt for customizable open-source clients.