mcp vs grafbase
mcp: AWS MCP Servers are a collection of specialized servers designed to integrate the Model Context Protocol (MCP) with AWS services, providing large language models with real-time access to AWS documentation, best practices, and operational capabilities. This enhances AI applications by improving output quality, enabling workflow automation, and offering deep domain knowledge for cloud-native development.; grafbase: Grafbase is a self-hosted, Rust-powered GraphQL Federation Gateway for high-scale, mission-critical applications. It unifies diverse data sources and microservices into a single, performant GraphQL API, offering enterprise-grade security and flexible deployment options.
TL;DR
- Your team builds on AWS and wants official AWS Labs MCP servers for up-to-date AWS docs, CDK/Terraform IaC, EKS/ECS containers, databases, and cost analysis.
- You use Cursor, VS Code, or Claude and want grounded AWS architecture and billing answers.
- You want a single SQL engine to query and audit resources across AWS, GCP, Azure, and SaaS providers together; StackQL is designed for multi-cloud SQL.
- You need native Streamable HTTP on individual local servers today (the local servers in this repo currently use stdio).
- You want a high-performance Rust Apollo Federation v2 GraphQL gateway that can expose your federated graph directly as an MCP server.
- You want to unify GraphQL subgraphs, REST, gRPC, Postgres, and Kafka using WebAssembly extensions in a self-hosted gateway.
- You do not use GraphQL and just want a proxy/gateway in front of existing MCP servers; use MCP Gateways like AgentGateway or MetaMCP.
- You want to write custom MCP tools in Python; use FastMCP or the MCP Python SDK.
Side-by-Side Comparison
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