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api-design
17 postsMCP Design Patterns: 6 Architectures for AI Tool Servers
Six practical MCP server architectures: API wrapper, composite service, resource-oriented, agent-backed, event-driven, and gateway patterns explained.
Progress Bar Is Not an API: Separating CLI UI from Events
Co-op Translator v0.20.0 separates its Rich CLI UI from a structured event stream, freeing integrations from parsing fragile console text.
What Breaks MCP Servers in Production
A look at real production failures in MCP servers—model-unreadable errors, token rotation logouts, schema key rejections, size limits—and the standard built to fix them.
CommitBrief — AI code reviews, right in your terminal
A provider-agnostic, local-first CLI that reviews your staged changes, a historic range, or a whole GitHub pull request. Zero telemetry, no server. Free and open source.
commitbrief.comWiring GA4 into an MCP Server: Making Analytics AI-Agent Friendly
GSC Wizard's MCP server GA4 integration reveals tricky engineering: detecting AI assistant traffic, token rotation, quota locks, and dual-client rendering.
Designing UX Without a Screen: Lessons from an MCP Server
A developer shares how building an MCP server forced UX decisions into tool names, schemas and auth design—with no screen, buttons or visual cues to rely on.
Lessons Learned Designing MCP Tools for AI Agents
How the FlurryPORT developer discovered why AI agents ignored their MCP tools, and the practical design lessons that fixed it.
Why Startups Shouldn't Go Direct to a Single AI Provider
Locking a startup's stack to one AI provider creates costly technical debt. OpenAI-compatible, multi-provider APIs offer a cheaper, more flexible alternative for engineering teams.