mcp-server-development

To connect Claude to your database, build an MCP server that defines typed tools and publishes read-only resources like jobs://list. This allows the AI to securely query data and perform actions without brittle manual API bridges.

The best way to expose typed tools to an AI assistant is defining callable functions with typed parameters, clear descriptions, and idempotency within an MCP server. This ensures reliable, auditable actions like CreateFactoryOrder.

Yes, you can build an MCP server using Python with FastMCP, TypeScript with the Model Context Protocol SDK, or C# with ASP.NET. These provide patterns for transports, error handling, and configuration hooks.

JSON-RPC transport for AI integrations works by implementing structured communication channels between the assistant and your server. It enables secure, typed function calls and contextual resource retrieval alongside standard stdio transports.

You need to publish read-only resources in an MCP server when providing contextual data for retrieval, such as drawings://metadata. This gives the AI safe access to reference information without exposing mutation endpoints.

For secure AI tool exposure, follow design principles emphasizing clear descriptions, typed inputs, idempotency, structured errors, and permission checks. This makes your integrations reliable and auditable.