Resumen del Artículo
The Model Context Protocol (MCP) defines how AI assistants, acting as clients, communicate with external tools and resources, functioning as MCP servers. This interaction often involves HTTP/1.1 or HTTP/2 for transport, using `application/jsonl` for streaming requests and responses.
- MCP communication features a client-initiated request stream and a server-initiated response stream, with tools needing to respond within a stipulated 'response buffer time' to avoid timeouts.
- Failure modes are diverse, including transport errors, malformed messages, tool execution errors, and invalid data schema, all requiring robust error handling.
- The article highlights the complexity of building reliable MCP integrations due to asynchronous operations, potential network issues, and the need for careful state management across multiple requests.
- Best practices for MCP server development include idempotent operations, careful handling of partial responses, and thorough validation of incoming and outgoing data.