Building Production-Ready LLM Integrations With MCP Over gRPC
summary
Argues that Model Context Protocol (MCP) works best when carried over bidirectional gRPC streaming, giving you existing gRPC features for auth, load balancing, tracing and deadlines. Describes three deployment patterns: HTTP/stdio-to-gRPC gateway (implemented as a prototype), a local stdio binary adapter, and an Envoy plugin planned. Recommends transcoding prompts/resources to protobuf while keeping tool payloads as JSON for flexibility, and targets a Python gRPC-enabled MCP SDK proof‑of‑concept around October/November.
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chapters (10)
- 0:00MCP and gRPC integration
- 1:03Overview of Model Context Protocol basics
- 3:31MCP payloads and API
- 6:23Why gRPC for MCP
- 9:15gRPC-MCP deployment models
- 11:23Transcoding trade-offs
- 13:57gRPC transport for MCP
- 16:43Q&A
- 18:50Service discovery in MCP
- 21:41Future plans and timeline
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