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September 18, 2025

Key Discussions

Vercel MCP-to-AI-SDK Launch

Vercel released a new library called mcp-to-ai-sdk that enables introspection and inlining of MCP servers. This tool allows developers to:

  • Convert MCP server capabilities into static tool definitions
  • Scope to specific/strict tool contracts
  • Modify available functionality more easily
  • Maintain MCP calls while providing better integration control

The library was successfully tested with the official Notion MCP server, demonstrating its practical utility for integrating MCP capabilities into applications.

Tldraw SDK Recognition and Integration

Tldraw featured the original branching chats demo in their latest release notes and provided a starter kit for creating similar whiteboard experiences. This recognition led to immediate integration work, with Tldraw being successfully incorporated into the MCP Client experiment.

Project Updates

MCP Client Enhancements

  • Tldraw Integration: Successfully integrated Tldraw whiteboard SDK into the MCP Client
  • Interactive Capabilities: Added visual collaboration features to the MCP development environment
  • Video Documentation: Created demonstration video showcasing the new capabilities

Future Development Considerations

  • Caret Application: The MCP-to-AI-SDK could be valuable for future Caret iterations, enabling inline integration of official remote MCP servers
  • Tool Definition Management: Static tool definitions could simplify MCP server integration workflows

Technical Highlights

MCP-to-AI-SDK Architecture

  • Wraps existing MCP servers while maintaining call functionality
  • Converts dynamic tool definitions to static contracts
  • Enables more granular control over available tool sets
  • Bridges gap between MCP flexibility and application-specific needs

Tldraw Whiteboard Integration

  • Real-time collaborative whiteboard capabilities
  • Visual representation of MCP interactions
  • Enhanced user experience for MCP development workflows

Resources Shared

Themes & Insights

MCP Ecosystem Maturation

The emergence of tools like MCP-to-AI-SDK indicates growing ecosystem support and recognition of MCP's potential. The ability to create static tool definitions addresses practical integration challenges while maintaining MCP's core benefits.

Visual Development Environments

The integration of whiteboard capabilities into development tools reflects a trend toward more visual, collaborative development experiences. This approach could enhance understanding and communication around complex MCP server interactions.

Community Recognition

External recognition from established tools like Tldraw validates the innovative approaches being developed within the community and suggests broader industry interest in these patterns.