Model Bridge
A no-code solution that bridges the gap between traditional OpenAPI-based services and the emerging MCP (Model Context Protocol) ecosystem, enabling seamless integration with AI/LLM clients.
The Challenge
Bridging Traditional APIs and AI Ecosystems
Complex MCP Integration
AI/LLM clients like Claude and Cursor require MCP servers, but most existing APIs use OpenAPI specifications, creating an integration gap.
Protocol Translation
Converting between HTTP REST APIs and MCP protocol with different transport mechanisms (HTTP, SSE) requires technical expertise.
Manual Configuration
Setting up tools, resources, and prompts for MCP servers typically requires extensive manual configuration and coding.
Billing Complexity
Monetizing MCP servers requires understanding both the MCP protocol and implementing billing systems from scratch.
Our Solution
From OpenAPI to MCP in Minutes
API Analysis & Mapping
Analyze existing OpenAPI specifications and automatically detect endpoints that can be exposed as MCP tools and resources.
No-Code Configuration
Provide intuitive interface for selecting which API endpoints to expose, configuring parameters, and customizing the MCP server behavior.
Protocol Translation
Implement seamless translation between OpenAPI REST calls and MCP protocol, handling different transport mechanisms (HTTP, SSE).
Middleware Integration
Add essential middleware layers including logging, rate limiting, authentication, and future on-demand billing capabilities.
Cloud Deployment
Deploy on Google Cloud Kubernetes infrastructure with automatic scaling and monitoring for production-ready MCP servers.
Key Benefits
Empowering AI Integration
Zero-Code MCP Integration
Transform any OpenAPI-based service into an MCP server without writing a single line of code.
AI Client Compatibility
Works seamlessly with Claude, Cursor, and other conversational AI platforms that support MCP protocol.
Automatic Detection
Intelligently analyzes OpenAPI specs to automatically configure tools, resources, and prompts.
Production Ready
Built-in middleware for logging, rate limiting, authentication, and future billing capabilities.
Flexible Configuration
Full control over which endpoints to expose and how they're mapped to MCP protocol.
Scalable Infrastructure
Hosted on Google Cloud Kubernetes with automatic scaling and enterprise-grade reliability.
Technology Stack
Built for Scale and Reliability
Core Technologies
- TypeScript: Type-safe development
- Node.js: Runtime environment
- OpenAPI Specification: API documentation standard
- MCP Protocol: Model Context Protocol for AI
Infrastructure & Deployment
- Google Cloud Platform: Cloud hosting platform
- Kubernetes: Container orchestration
- Docker: Containerization
- HTTP/SSE Transport: Communication protocols
Security & Middleware
- API Gateway: Request routing and management
- Rate Limiting: Traffic control
- Authentication: Access control
- Logging & Monitoring: Observability
Ready to Bridge Your APIs?
Transform your existing APIs into AI-ready MCP servers