Elevator pitch
Build your own Model Context Protocol server to extend AI capabilities with custom tools and data sources.
Industry
AI Infrastructure & Developer Tools
Problem
- AI models lack access to proprietary data and custom business logic.
- Integrating external tools requires repetitive, fragmented implementations.
Solution
- Create a reusable MCP server that standardizes tool exposure to Claude and other AI clients.
- Connect any data source or API once; use it everywhere AI runs.
Tools
schema-validator: Validates MCP tool definitions against protocol spec (JSON schema → validation report)context-injector: Injects system prompts and tool metadata into conversation context (config → enriched context)transport-adapter: Bridges stdio, SSE, or custom transports (protocol type → connection handler)
Widgets
/dashboard: Real-time tool registry and request/response logging interface
Conversation starters
- "How do I expose my database as an MCP tool?"
- "What's the best way to handle authentication in my custom MCP server?"