Case Studies

Real Projects, Real Results

See how AI-native development delivers measurable business value. From MCP integrations to multi-agent systems, these case studies showcase practical implementations and their outcomes.

MCP Server for Gamma Presentations

Open Source • Model Context Protocol • TypeScript

Challenge: AI assistants lacked direct integration with Gamma, a popular presentation platform. Users had to manually copy content between tools, breaking their workflow and reducing productivity.

Solution: Developed a production-ready MCP server that connects AI assistants (Claude Desktop, Cursor, etc.) directly to the Gamma API. The server enables AI to create, update, and manage presentations programmatically.

Key Features:

  • Create new presentations with AI-generated content
  • Update existing slides programmatically
  • Search and retrieve presentation data
  • Full TypeScript implementation with comprehensive error handling
  • Complete documentation and usage examples

Results:

  • 500+ npm downloads in first month after release
  • Open sourced on GitHub, benefiting the entire MCP community
  • Zero production issues reported by users
  • Active community contributions and feature requests

Technologies: TypeScript, Model Context Protocol, Gamma API, npm packaging

View on GitHub →

Awesome Comparisons — Developer Resource

Open Source • Documentation • Community Resource

Challenge: Developers struggling to choose between rapidly evolving AI tools, frameworks, and services. Information scattered across blog posts, documentation, and marketing materials made objective comparison difficult.

Solution: Created a curated comparison framework documenting AI tools, coding assistants, and development frameworks. Structured tables enable side-by-side feature comparison with objective criteria.

Key Features:

  • Side-by-side comparisons of major AI coding assistants
  • Framework evaluations (CrewAI, LangChain, AutoGen, etc.)
  • Updated regularly as tools evolve
  • Community-driven with contribution guidelines
  • Markdown format for easy updates and version control

Results:

  • Referenced by developer communities for tool selection
  • Active community engagement with suggestions and updates
  • Helps developers make informed decisions based on objective criteria
  • Growing resource as AI tooling ecosystem expands

Technologies: Markdown, Documentation, GitHub

View on GitHub →

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