Model Context Protocol (MCP), SSE, and STDIO Server – Fastn.ai
Solo project – full system architecture and implementation
I engineered a unified backend infrastructure that powers real-time, context-aware AI interactions, enabling seamless communication between AI models and 1500+ external tools and services.
✅ Core Capabilities
Interactive AI Chat with Streaming UI
Built a responsive, real-time chat system that delivers live streaming responses from connected AI models.
Multi-Model AI Support
Integrated advanced models including GPT-4o, GPT-4 Turbo, GPT-3.5 Turbo, Gemini 1.5 Pro, Gemini Flash (1.5/2.0), and O3-mini —all accessible through one server.
Tool Integration with 1500+ Platforms
Connected AI workflows to popular tools such as Microsoft Teams, Slack, Gmail, Google Calendar, Google Sheets, HubSpot, Jira, Linear, Notion, and many more—enabling complex task automation via the Fastn platform.
MCP, SSE, and STDIO Protocol Servers
Developed three communication layers to handle context passing, real-time streaming (SSE), and CLI-based tool execution (STDIO), offering broad interoperability across environments.
Persistent Conversation Management
Ensured long-term memory and context tracking between sessions, enhancing the AI's continuity and usefulness.
Authentication & Access Control
Implemented secure login systems and token management for protected, user-specific experiences.
Scalable Cross-Platform Support
Optimized for integration with platforms like Claude.ai and Cursor.ai, while remaining easily extendable to new services.
This system empowers AI agents with real-time capabilities, cross-tool execution, and long-term context memory—delivering enterprise-grade intelligence for modern automation needs.
Built a real-time AI server supporting GPT & Gemini models, 1500+ tool integrations (Slack, Teams, Jira, etc.), context-aware chat, and MCP/SSE/STDIO protocols.